The Orocos Component Builder's Manual

Open RObot COntrol Software


Orocos Version 1.0.4.

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.1 or any later version published by the Free Software Foundation, with no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts. A copy of this license can be found at


This document gives an introduction to building your own components for the Orocos ( Open RObot COntrol Software ) project.

Table of Contents

1. How to Read this Manual
1. Component Interfaces
2. Component Implementation
3. Orocos Real-Time Toolkit Overview
4. Orocos Real-Time Toolkit Software Structure
2. Setting up the Component Interface
1. Introduction
2. Hello World !
3. Setting Up a Basic Task
3.1. Task Application Code
3.2. Starting Task Execution
3.3. Interfacing the TaskContext
3.4. Introducing the TaskContext's Interface
3.5. The Data Flow Interface
3.6. The Method Interface
3.7. Method Argument and Return Types
3.8. The Attributes and Properties Interface
3.9. The Command Interface
3.10. The Event Interface
4. Connecting TaskContexts
4.1. Setting up the Execution Flow
4.2. Setting up the Data Flow
4.3. Disconnecting Tasks
5. Deploying Components
5.1. Overview
5.2. Embedded TaskCore Deployment
5.3. Embedded TaskContext Deployment: C++ Interface
5.4. Full TaskContext Deployment: Dynamic Interface
5.5. Putting it together
6. Using Tasks
6.1. Task Property Configuration
6.2. Task Scripts
7. Advanced Techniques
7.1. Using the TaskContext
7.2. Wrapping Methods in Functions
7.3. Waiting for Something : Synchronisation
7.4. Polymorphism : Task Interfaces
3. Orocos Scripting Reference
1. Introduction
2. General Scripting Concepts
2.2. Identifiers
2.3. Expressions
2.4. Parsing and Loading Programs
3. Orocos Program Scripts
3.1. Program Execution Semantics
3.2. Program Syntax
3.3. Starting and Stopping Programs from scripts
4. Orocos State Descriptions : The Real-Time State Machine
4.1. Introduction
4.2. StateMachine Workings
4.3. Parsing and Loading StateMachines
4.4. Defining StateMachines
4.5. Instantiating Machines: SubMachines and RootMachines
4.6. Starting and Stopping StateMachines from scripts
5. Program and State Example
4. Distributing Orocos Components with CORBA
1. Overview
1.1. Status
1.2. Requirements and Setup
1.3. Limitations
2. Code Examples
3. Usage
4. Orocos Corba Interfaces
5. Core Library Reference
1. Introduction
2. Periodic and non Periodic Activities
2.1. Creating a Periodic Activity
2.2. Periodic Activity Ordering
2.3. Example Periodic Activity Creation
2.4. Non Periodic Activities
2.5. Custom or Slave Activities
2.6. Accessing the Threads from Activities
2.7. Simulation
3. Commands
3.1. The Command Processor
4. Events
4.1. Event Basics
4.2. setup() and the Handle object
4.3. Choosing the Asynchronous Thread
4.4. Event Overrun Policy
4.5. The Completion Processor
5. Time Measurement and Conversion
5.1. The TimeService
5.2. Usage Example
6. Attributes
7. Properties
7.1. Introduction
7.2. Grouping Properties in a PropertyBag
7.3. Marshalling and Demarshalling Properties (Serialization)
8. The NameServer
8.1. Introduction
8.2. Using the NameServer
9. Buffers and DataObjects
9.1. Buffers
9.2. DataObjects
10. Logging
6. OS Abstraction Reference
1. Introduction
1.1. Realtime OS Abstraction
2. The Operating System Interface
2.1. Basics
3. OS Package Structure
3.1. The RTAI/LXRT OS target
3.2. Porting Orocos to other Architectures / OS'es
3.3. OS Header Files
4. Using Threads and Realtime Execution of Your Program
4.1. Writing the Program main()
4.2. The Orocos Thread System
4.3. Synchronisation Primitives
7. Hardware Device Interfaces
1. The Orocos Device Interface (DI)
2. The Device Interface Classes
2.1. Physical IO
2.2. Logical Device Interfaces
3. Porting Device Drivers to Device Interfaces
4. Interface Name Serving

List of Figures

1.1. Orocos as Middleware
1.2. Real-Time Toolkit Layers
2.1. Tasks Run in Threads
2.2. Schematic Overview of a TaskContext
2.3. Schematic Overview of the Hello Component.
2.4. Schematic Overview of a TaskContext
2.5. Executing a TaskContext
2.6. Component Deployment Levels
2.7. Example Component Deployment.
3.1. State Change Semantics in Reactive Mode
3.2. State Change Semantics in Automatic Mode
5.1. Execution sequence diagram
5.2. Tasks Sending Commands
5.3. Event Handling
5.4. DataObjects versus Buffers
6.1. OS Interface overview
7.1. Device Interface Overview

List of Tables

2.1. Method Return & Argument Types
3.1. array and string constructors
5.1. Thread and Activity summary
5.2. Logger Log Levels
6.1. Header Files
7.1. Physical IO Classes

List of Examples

2.1. TaskContext Data Flow Topology Example
2.2. TaskContext Peer Disconnection Example
3.1. string and array creation
3.2. StateMachine Definition Format
3.3. StateMachine Example (state.osd)
3.4. Program example (program.ops)
5.1. Example Periodic Activity Creation
5.2. Example Periodic Thread Interaction
5.3. Using Events
5.4. Event Types
5.5. Creating attributes
5.6. Using properties
5.7. Accessing a Buffer
5.8. Accessing a DataObject
5.9. Using the Logger class
6.1. Locking a Mutex
7.1. Using the name service

Chapter 1. How to Read this Manual

This manual is for Software developers who wish to write their own software components using the Orocos Real-Time Toolkit. The possible communication primitives between components is defined and implemented in the Orocos Core Library (CoreLib). You can find the CoreLib Reference Chapter at the end to find out the precise semantics of our communication primitives. The Orocos hardware abstraction is included as well.

1. Component Interfaces

The most important Chapters to get started building a component are presented first. Orocos components are implemented using the 'TaskContext' class and the following Chapter explains step by step how to define the interface of your component, such that you can interact with your component from a user interface or other component.

2. Component Implementation

For implementing algorithms within your component, the Orocos Scripting Chapter details how to write programs and state machines. "Advanced Users" may benefit from this Chapter as well since the scripting language allows to 'program' components without recompiling the source.

3. Orocos Real-Time Toolkit Overview

The Real-Time Toolkit allows deployment, distribution and the building of real-time software components. It is sometimes refered to as 'middleware' because it sits between the application and the Operating System. It takes care of the real-time communication and execution of software components.

Figure 1.1.  Orocos as Middleware

Orocos as Middleware

4. Orocos Real-Time Toolkit Software Structure

The Real-Time Toolkit is structured in layers on top of the hardware target (CPU) and the devices (IO) and encompasses some libraries.

Figure 1.2.  Real-Time Toolkit Layers

Real-Time Toolkit Layers

All Orocos software communicates through Operating System abstractions with the underlying OS or through Device Interfaces with the IO hardware. On the left side on top of the OS Abstraction is the Core Library, which presents infrastructure for writing realtime (periodic) activities, including many communication primitives. On top of that is the Real-Time Toolkit, which allows to define browsable components which are capable of receiving (remote) commands, process programs and hierarchical state machines and share realtime data with other components. Your application may use that infrastructure to define its own components and set up communication between them.

On the right side, lives the Device Abstraction stack. The Operating System already provides a device driver model, Orocos device drivers map that model to machine or robot control specific Device Interfaces. An Orocos Device combines a number of these interfaces into an object representing a physical entity. It may represent a complete machine, or just a mere Sensor or Axis, such that your application can communicate with physical meaningful devices ( instead of IO ports).

Because of the Openness of Orocos, your application does not need to take-all-or-leave-all. You can pick out the level of abstraction which suits you best for a given application (indicated by the gradient).

Chapter 2. Setting up the Component Interface


This document describes the Orocos Task Infrastructure, which allows to design Real-Time tasks which transparantly communicate with each other.

1. Introduction

This manual documents how multi-threaded components can be defined in Orocos such that they form a thread-safe robotics/machine control application. Each control component is defined as a "TaskContext", which defines the "context" in which the component task is executed. The context is built by the five Orocos primitives: Event, Property, Command, Method and Data Port. This document defines how a user can write his own task context and how it can be used in an application.

Figure 2.1.  Tasks Run in Threads

Tasks Run in Threads

Tasks run in (periodic) threads.

A task is a basic unit of functionality which executes one or more (real-time) programs in a single thread. The program can vary from a mere C function over a real-time program script to a real-time hierarchical state machine. The focus is completely on thread-safe time determinism. Meaning, that the system is free of priority-inversions, and all operations are lock-free (also data sharing and other forms of communication such as events and commands). Real-time tasks can communicate with non real-time tasks (and vice versa) transparantly.

The Orocos Task Infrastructure enables :

  • Lock free, thread-safe, inter-thread function calls.

  • Communication between hard Real-Time and non Real-Time threads.

  • Deterministic execution time during communication for the higher priority thread.

  • Synchronous and asynchronous communication between threads.

  • Interfaces for component distribution.

  • C++ class implementations for all the above.

This document relates to other manuals as such :

Core Library

provides the Event infrastructure, activity to thread mapping, Properties and lock-free data exchange implementations.

Execution Engine

provides a real-time program execution framework. It executes the real-time programs which interact with other tasks.

Program Parser

provides a scripting language which is convertible to a form which can be accepted by the Execution Engine.

The Scripting manual gives more details about script syntax for state machines and programs.

Figure 2.2.  Schematic Overview of a TaskContext

Schematic Overview of a TaskContext

The Execution Flow is formed by Programs and State Machines sending commands, events,... to Peer Tasks. The Data Flow is the propagation of data from one task to another, where one producer can have multiple consumers and vice versa.

A task's interface consists of : Attributes and Properties, Commands, Methods, Events and Data Flow ports which are all public. The class TaskContext groups all these interfaces and serves as the basic building block of applications. A component developer 'builds' these interfaces using the instructions found in this manual.

2. Hello World !

This section introduces tasks through the "hello world" application, which can be downloaded from It contains one TaskContext component which has one instance of each communication primitive.

Figure 2.3.  Schematic Overview of the Hello Component.

Schematic Overview of the Hello Component.

Our hello world task.

The way we interact with TaskContexts during development of an Orocos application is through the Task Browser. The TaskBrowser is a powerful console tool which helps you to explore, execute and debug TaskContexts in running programs. All you have to do is to create a TaskBrowser and call its loop() method. When the program is started from a console, the TaskBrowser takes over user input and output.


The OCL::TaskBrowser is a component of its own which is found in the Orocos Component Library (OCL).

  #include <ocl/TaskBrowser.hpp>
  #include <rtt/os/main.h>
  // ...

  using namespace Orocos;

  int ORO_main( int, char** )
      // Create your tasks
      TaskContext* task = ...

      // when all is setup :
      TaskBrowser tbrowser( task );

      return 0;

The TaskBrowser uses the GNU readline library to easily enter commands to the tasks in your system. This means you can press TAB to complete your commands or press the up arrow to scroll through previous commands.

0.016 [ Info   ][main()] ./helloworld manually raises LogLevel to 'Info' (5). See also file 'orocos.log'.
0.017 [ Info   ][main()] **** Creating the 'Hello' component ****
0.018 [ Info   ][ConnectionC] Creating Asyn connection to the_event.
0.018 [ Info   ][ExecutionEngine::setActivity] Hello is periodic.
0.019 [ Info   ][main()] **** Starting the 'Hello' component ****
0.019 [ Info   ][main()] **** Using the 'Hello' component    ****
0.019 [ Info   ][main()] **** Reading a Property:            ****
0.019 [ Info   ][main()]      the_property = Hello World
0.019 [ Info   ][main()] **** Sending a Command:             ****
0.020 [ Info   ][main()]      Sending the_command : 1
0.020 [ Info   ][main()] **** Calling a Method:              ****
0.020 [ Info   ][main()]      Calling the_Method : Hello World
0.020 [ Info   ][main()] **** Emitting an Event:             ****
0.021 [ Info   ][main()] **** Starting the TaskBrowser       ****
0.021 [ Info   ][TaskBrowser] Creating a BufferConnection from the_buffer_port to the_buffer_port with size 13
0.021 [ Info   ][TaskBrowser] Connected Port the_buffer_port to peer Task Hello.
0.022 [ Info   ][Hello] Creating a DataConnection from the_data_port to the_data_port
0.022 [ Info   ][Hello] Connected Port the_data_port to peer Task TaskBrowser.
   Switched to : Hello
0.023 [ Info   ][main()] Entering Task Hello
0.023 [ Info   ][Hello] Hello Command: World
0.023 [ Info   ][Hello] Receiving Event: Hello World

  This console reader allows you to browse and manipulate TaskContexts.
  You can type in a command, event, method, expression or change variables.
  (type 'help' for instructions)
    TAB completion and HISTORY is available ('bash' like)

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :                                                     

The first [ Info ] lines are printed by the Orocos Logger, which has been configured to display informative messages to console. Normally, only warnings or worse are displayed by Orocos. You can always watch the log file 'orocos.log' in the same directory to see all messages. After the [Log Level], the [Origin] of the message is printed, and finally the message itself. These messages leave a trace of what was going on in the main() function before the prompt apeared.

Depending on what you type, the TaskBrowser will act differently. The built-in commands cd, help, quit and ls are seen as commands to the TaskBrowser itself, if you typed something else, it tries to evaluate your command to an expression and will print the result to the console. If you did not type an expression, it tries to parse it as a command to a (peer) task. If that also fails, it means you made a typo and it prints the syntax error to console.

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :1+1
      Got :1+1
   = 2

To display the contents of the current task, type ls, and switch to one of the listed peers with cd, while cd .. takes you one peer back in history. Since there are no peers other than the TaskBrowser itself, one can not cd anywhere in this example.

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :ls

 Listing Hello :

 Attributes   :
 (Attribute)      string the_attribute      = Hello World
 (Attribute)      string the_constant       = Hello World
 (Property )      string the_property       = Hello World          (Hello World Description)

 Interface    :
  Methods      : the_method isRunning start stop trigger update
  Commands     : the_command
  Events       : the_event

 Objects      :
            this (  )
   the_data_port ( A Task Object. )
 the_buffer_port ( A Task Object. )

 Ports        : the_data_port the_bufferPort
 Peers        : TaskBrowser

To get a quick overview of the commands, type help.

First you get a list of the Properties and Attributes (alphabetical) of the current component. Properties are meant for configuration and can be written to disk. Attributes are solely for run-time values. Each of them can be changed (except constants.)

Next, the interface of this component is listed: One method is present the_method, one command the_command and one event the_event. They all print a 'Hello World' string when invoked.

In the example, the current task has only three objects: this, the_data_port and the_buffer_port. The this object serves as the public interface of the Hello component. These objects contain methods, commands or events. The next two objects are created to represent the data ports of the Hello component and contain the operations to send or receive data or query connection status.

Last, the peers are shown, that is, the components which are connected to this component. The HelloWorld component is a stand-alone component and has only the TaskBrowser as a peer.

To get a list of the Task's interface, you can always type an object name, for example this.

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) : this
      Got :this

Printing Interface of 'Hello' :

  Command    : bool the_command( string the_arg )
   Hello Command Description
   the_arg : Use 'World' as argument to make the command succeed.
  Method     : string the_method( )
   Hello Method Description
  Event     : void the_Event( string the_data )
   Hello Event Description
   the_data : The data of this event.

Now we get more details about the commands, methods and events registered in the public interface. We see now that the the_command command takes one argument as a string, or that the the_method method returns a string. One can invoke each one of them:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_method()
      Got :the_method()
 = Hello World

Methods are called directly and the TaskBrowser prints the result. The return value of the_method() was a string, which is "Hello World".

When a command is entered, it is sent to the Hello component, which will execute it on behalf of the sender. The different stages of its lifetime are displayed by the prompt. Hitting enter will refresh the status line:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_command("World")
      Got :the_command("World")

 In Task Hello. (Status of last Command : queued)
1021.835 [ Info   ][Hello] Hello Command: World
 (type 'ls' for context info) :                   

1259.900 [ Info   ][main()] Checking Command: World
 In Task Hello. (Status of last Command : done )
 (type 'ls' for context info) :                   

A Command might be rejected (return false) in case it received invalid arguments:

 In Task Hello. (Status of last Command : done )
 (type 'ls' for context info) :the_command("Belgium")
      Got :the_command("Belgium")

 In Task Hello. (Status of last Command : queued )
 (type 'ls' for context info) :
1364.505 [ Info   ][Hello] Hello Command: Belgium

 In Task Hello. (Status of last Command : fail )
 (type 'ls' for context info) :         

Besides sending commands to tasks, you can alter the attributes of any task, program or state machine. The TaskBrowser will confirm validity of the assignment with 'true' or 'false' :

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_attribute
      Got :the_attribute
 = Hello World
 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_attribute = "Veni Vidi Vici !"
      Got :the_attribute = "Veni Vidi Vici !"
 = true

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_attribute
      Got :the_attribute
 = Veni Vidi Vici !

Finally, let's emit an Event. The Hello World Event requires a payload. A callback handler was registered by the component, thus when we emit it, it can react to it:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_event(the_attribute)
      Got :the_event(the_attribute)
 = true
 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :
354.592 [ Info   ][Hello] Receiving Event: Veni Vidi Vici !

The example above passed the the_attribute object as an argument to the event, and it was received by our task correctly. Events are related to commands, but allow broadcasting of data, while a command has a designated receiver.

The Data Ports can be accessed through the the_data_port and the_buffer_port object interfaces. Once again, we can inspect the interface of an object by typing its name:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_data_port
      Got :the_data_port

Printing Interface of 'the_data_port' :

  Method     : string Get( )
   Get the current value of this Data Port
  Method     : void Set( string const& Value )
   Set the current value of this Data Port
   Value : The new value.

The the_data_port object has two methods: Get() and Set(). Since data ports are used for sending unbuffered data packets between components, this makes sense. One can interact with the ports as such:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_data_port.Set("World")
      Got :the_data_port.Set("World")
 = (void)

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :the_data_port.Get()
      Got :the_data_port.Get()
 = World

When a value is Set(), it is sent to whatever is connected to that port, when we read the port using Get(), we see that the previously set value is present. The advantage of using ports is that they are completely thread-safe for reading and writing, without requiring user code. The Hello component also contains a the_buffer_port for buffered data transfer. You are encouraged to play with that port as well.

Remember that the TaskBrowser was a component as well ? When a user enters ls, the interface of the visited component is listed. It is also possible to get an 'outside' view of the visited component, through the eyes of an external component. The leave allows a view from within the TaskBrowser itself:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :leave
1001.607 [ Info   ][main()] Watching Task Hello

 Watching Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :ls

 Listing TaskBrowser :

 Attributes   : (none)

 Interface    :
  Methods      : isRunning start stop trigger update
  Commands     : (none)
  Events       : (none)

 Objects      :
            this (  )
        the_data_port ( A Task Object. )
      the_buffer_port ( A Task Object. )

 Ports        : the_data_port the_buffer_port
 Hello Peers : TaskBrowser

The following things are noteworthy: 'ls' shows now the contents of the TaskBrowser itself and no longer of the Hello Component. The TaskBrowser has the same ports as the component it visist: the_data_port and the_buffer_port. These were created at run-time and allow to write or read ports from the visited component.

One can enter the 'inside' view again by entering enter:

 Watching Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :enter
1322.653 [ Info   ][main()] Entering Task Hello

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :      

Last but not least, hitting TAB twice, will show you a list of possible completions, such as peers or commands :

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :
the_attribute     the_event         cd ..         quit
the_buffer_port.  the_method        help          this.
the_command       the_property      leave
the_constant      TaskBrowser.  list
the_data_port.     cd            ls
 (type 'ls' for context info) : 

TAB completion works even across peers, such that you can type a TAB completed command to another peer than the current peer.

In order to quit the TaskBrowser, enter quit:

 In Task Hello. (Status of last Command : none )
 (type 'ls' for context info) :quit

1575.720 [ Info   ][ExecutionEngine::setActivity] Hello is disconnected from its activity.
1575.741 [ Info   ][Logger] Orocos Logging Deactivated.      

The TaskBrowser Component is application independent, so that your enduser-application might need a more suitable interface. However, for testing and inspecting what is happening inside your real-time programs, it is a very useful tool. The next sections show how you can add properties, commands, methods etc to a TaskContext.


If you want a more in-depth tutorial, see the 'task-intro' example for a TaskBrowser which visits a network of three TaskContexts.

3. Setting Up a Basic Task

Tasks are implemented by the TaskContext class. It is useful speaking of a context because it defines the context in which an activity (a program) operates. It defines the interface of the task, its properties, its peer tasks and uses its ExecutionEngine to handle its programs and to accept commands from other tasks.

This section walks you through the definition of an example task in order to show you how you could build your own task.


The ready-to-execute code of this section can be found in the 'simple-task' package on the RTT Download section of the website.

A TaskContext is constructed as :

  #include <rtt/TaskContext.hpp>

  // we assume this is done in all the following code listings :
  using namespace RTT;

  TaskContext a_task("ATask");

The argument is the (unique) name of the task.

A task's interface consists of : Commands, Methods, Ports, Attributes and Properties and Events, which are all public. We will refer to them as members.

Figure 2.4.  Schematic Overview of a TaskContext

Schematic Overview of a TaskContext

The Execution Flow is formed by Programs and State Machines using the interface of Peer Tasks. The Data Flow is the propagation of data from one task to another, where one producer can have multiple consumers.

When a TaskContext is running, it accepts commands or events using its Execution Engine. The Execution Engine will check periodically for new commands in it's queue and execute programs which are running in the task. Thus to start using the task, one needs to start the Execution Engine. As long as it is not started, it will accept no commands, run no programs and react to no events.

3.1. Task Application Code

The user may insert his application code in the startup(), update() and shutdown() functions of a TaskContext by inheriting from that class.

  #include <rtt/TaskContext.hpp>
  class MyTask 
    : public TaskContext
       MyTask(std::string name) 
         : TaskContext(name)
          // see lateron what to put here.
        * This function contains the application's startup code.
	* Return false to abort startup.
       bool startup() {
          // ...
	  return true;

        * This function is periodically called.
       void update() {
          // Your algorithm for periodic execution goes inhere

        * This function is called when the task is stopped.
       void shutdown() {
          // Your cleanup code

When a TaskContext is started, startup() is called once and may abort the startup sequence by returning false, for example, because of misconfiguration. When all went well, update() is called (a)periodically by the ExecutionEngine, see below. When the task is stopped, shutdown() is called after the last update().

3.2. Starting Task Execution

The functionality of a task, i.e. its algorithm, is executed by the Execution Engine. To run an ExecutionEngine, you need to use one of the ActivityInterface classes from the CoreLib, for example PeriodicActivity or NonPeriodicActivity. This relation is shown in Figure 2.5, “ Executing a TaskContext ”.

Figure 2.5.  Executing a TaskContext

Executing a TaskContext

You can make a TaskContext '(re-)active' by creating an Activity object which executes its Execution Engine. The Execution Engine delegates all work to specific 'Processors' and user code in update().

The Activity classes will allocate a thread which executes the Execution Engine. The choosen ActivityInterface object will invoke the Execution Engine, which will in turn invoke the application's methods above.

  #include <rtt/PeriodicActivity.hpp>

  using namespace RTT;

  TaskContext* a_task = new MyTask("the_task")
  // create a periodic activity with priority=5, period=1000Hz
  PeriodicActivity act(5, 0.001, a_task->engine() );
  // ... start the execution engine of a_task :
  // ...

Which will run the Execution Engine of "ATask" with a timer frequency of 1kHz. This is the frequency at which state machines are evaluated, program steps taken, commands and events are accepted and executed and the application code is run. When the periodic activity is stopped again, all programs are stopped, state machines are brought into the final state and no more commands or events are accepted.

A TaskContext can also be run in a non periodic activity:

  #include <rtt/NonPeriodicActivity.hpp>

  using namespace RTT;

  TaskContext* a_task = new MyTask("the_task")
  // create a non periodic activity with priority=5
  NonPeriodicActivity nonpAct(5, a_task->engine() );
  // ... start the execution engine of a_task :
  // ...

In case the Execution Engine waits for new Commands or Events to come in to be executed. Each time such an event happens, the user's application code (update()) is called as well.


Non periodic activities should be used with care and with much thought. The ExecutionEngine will do absolutely nothing if no commands or asynchronous events come in. This may lead to surprising 'bugs' when program scripts or state machine scripts are executed, as they will only progress upon these events and seem to be stalled otherwise.

3.3. Interfacing the TaskContext

During development of your TaskContext, it is handy to connect the TaskBrowser to your task such that you can interactively manipulate it and it's properties:

  #include <ocl/TaskBrowser.hpp>
  // ... see above
  TaskBrowser browser(a_task);

  // Start the interactive console:

In which you can start/stop the task and manipulate every aspect of it's interface, as was seen in the previous section.

3.4. Introducing the TaskContext's Interface

A TaskContext exists of a number of accessor methods which expose a specific part of the interface. These methods are:


The meaning of these methods are explained in the following sections.

3.5. The Data Flow Interface


The 'Data Flow' is a 'stream of data' between tasks. A classical control loop can be implemented using the Data Flow interface. The data is passed buffered or unbuffered from one task to another.

The Orocos Data Flow is implemented with the Port-Connector software pattern. Each task defines its data exchange ports and inter-task connectors transmit data from one port to another. A Port is defined by a name, unique within that task, the data type it wants to exchange and the buffered or un-buffered method of exchanging. Buffered exchange is done by "Buffer" Ports and un-buffered exchange is done by "Data" Ports.

A Data Port can offer read-only, write-only or read-write access to the unbuffered data. A Buffer Port can offer read-only, write-only and read-write access to the buffered data. The example below shows all these possiblities.

3.5.1. Setting up the Data Flow Interface


The ready-to-execute code of this section can be found in the 'dataflow-task' package on the RTT Download page of the website.

Any kind of data can be exchanged (also user defined types) but for readability, only the 'double' C type is used here.

  #include <rtt/Ports.hpp>
  using namespace RTT;

  class MyTask
    : public TaskContext
    // Read-only data port:
    ReadDataPort<double> indatPort;
    // Write-only data port:
    WriteDataPort<double> outdatPort;
    // Read-Write data port:
    DataPort<double> rwdatPort;

    // Read-only buffer port:
    ReadBufferPort<double> inbufPort;
    // Write-only buffer port:
    WriteBufferPort<double> outbufPort;
    // Read-Write buffer port:
    BufferPort<double> rwbufPort;
    // ...
    MyTask(std::string name)
      : TaskContext(name),
	outdatPort("Data_W", 1.0),  // note: initial value
	rwdatPort("Data_RW", 1.0),

	outbufPort("Packet_1", 15), // note: buffer size
	rwbufPort("Packet_2", 30)
       this->ports()->addPort( &indatPort );
       this->ports()->addPort( &outdatPort );
       this->ports()->addPort( &rwdatPort );

       this->ports()->addPort( &inbufPort );
       this->ports()->addPort( &outbufPort );
       this->ports()->addPort( &rwbufPort );

       // more additions to follow, see below

     // ...

The example starts with declaring all the ports of MyTask. A template parameter specifies the type of data the task wants to exchange through that port. Logically, if two tasks are connected, they must agree on this type. The constructor of MyTask initialises each port with a name. This name is used to 'match' ports between connected tasks. Orocos will warn at run-time if names or types do not match.

Write and read-write Buffers take besides a name, the prefered buffer size as a parameter. In the example, these are the values 15 and 30. Before the task is connected to its peers, you can still change this value with the setBufferSize() function of the Port.

Finally, a 'write' port can take an initial value in the constructor as well. This value will be used when the connection between two ports is created in order to initialise the connection ( using 'connectPorts', see Section 4, “Connecting TaskContexts” ). If a 'write' port is connected to an existing connection, the initial value (and buffer size) are ignored and the settings of the existing connection are not touched. You can modify the initial value with the 'Set( value )' function in both Buffer and Data write ports.


Alternatively, you can connect buffers in your main() program by writing:

  #include <rtt/ConnectionFactory.hpp>
  // ...
  int buf_size = 100;
  ConnectionFactory<double> cf;
  ConnectionInterface::shared_ptr con =
  if (con)

before the tasks are connected. This connection will then take precedence.

3.5.2. Using the Data Flow Interface in C++

The Data Flow interface is used by your task from within the program scripts or its update() method. Logically the script or method reads the inbound data, calculates something and writes the outbound data.

  #include <rtt/Ports.hpp>
  using namespace RTT;

  class MyTask
    : public TaskContext
     // ...Constructor sets up Ports, see above.

     bool startup() {
       // Check validity of (all) Ports:
       if ( !indatPort.connected() ) {
          // No connection was made !
	  return false;
       if ( !outdatPort.connected() ) {
          // ...

     bool update() {
       // Read and write the Data Flow:
       // Unbuffered:
       double val = indatPort.Get();
       // calculate...
       outdatPort.Set( val );

       // Buffered:
       if ( inbufPort.Pop( val ) ) {
          // calculate...
       } else {
          // buffer empty.

       if ( outbufPort.Push( val ) ) {
          // ok.
       } else {
          // buffer full.
     // ...

It is wise to check in the startup() function if all necessary ports are connected() ( or ready() ). At this point, the task startup can still be aborted by returning false. Otherwise, a write to a port will be discarded, while a read returns the initial value or the default value. A Pop of a disconnected port will always return false.

3.5.3. Using Data Flow in Scripts

When a Port is connected, it becomes available to the Orocos scripting system such that (part of) the calculation can happen in a script. Also, the TaskBrowser can then be used to inspect the contents of the DataFlow online.

A small program script could be loaded into MyTask with the following contents:

  program MyControlProgram {
    double the_K  = K        // read task property, see later.
    double setp_d

    while ( true ) {
      if ( SetPoint_X.Pop( setp_d ) ) { // read Buffer Port
        double in_d = Data_R.Get()      // read Data Port
        double out_d = (setp_d - in_d) * K  // Calculate
        do Data_W.Set( out_d )          // write Data Port
      do nothing       // this is a 'wait' point.

The program "MyControlProgram" starts with declaring two variables and reading the task's Property 'K'. Then it goes into an endless loop, trying to Pop a setpoint value from the "SetPoint_X" Buffer Port. If that succeeds (buffer not empty) the "Data_R" Data Port is read and a simple calculation is done. The result is written to the "Data_W" Data Port and can now be read by the other end. Alternatively, the result may be directly used by the Task in order to write it to a device or any non-task object. You can use methods (below) to send data from scripts back to the C++ implementation.

Remark that the program is executed within the Execution Engine. In order to avoid the endless loop, a 'wait' point must be present. The "do nothing" command inserts such a wait point and is part of the Scripting syntax. If you plan to use Scripting state machines, such a while(true) loop and hence wait point is not necessary. See the Scripting Manual for a full overview of the syntax.

3.6. The Method Interface


A task's methods are intended to be called 'synchronously' by the caller, i.e. are directly executed like a function. Use it to 'calculate' a result or change a parameter.

The easiest way to access a TaskContext's interface is through Methods. They resemble very much normal C or C++ functions, but they have the advantage to be usable in scripting or can be called over a network connection. They take arguments and return a value. The return value can in return be used as an argument for other Methods or stored in a variable. For all details, we refer to the Orocos Scripting Manual.

To add a TaskContext's method to the method interface, one proceeds similarly as when creating Data Ports. The data type is now replaced by a function signature, for example '

void(int, double)

' which is the signature of a function returning 'void' and having two arguments: an 'int' and a 'double'.

  #include <rtt/Method.hpp>
  using namespace RTT;

  class MyTask
    : public TaskContext
    void reset() { ... }
    string getName() const { ... }
    double changeParameter(double f) { ... }
    // ...

    Method<void(void)> resetMethod;
    Method<string(void)> nameMethod;
    Method<double(double)> paramMethod;

    MyTask(std::string name)
      : TaskContext(name),
      resetMethod("reset", &MyTask::reset, this),
      nameMethod("name", &MyTask::getName, this),
      resetMethod("changeP", &MyTask::changeParameter, this)
       // Add the method objects to the method interface:
       this->methods()->addMethod( &resetMethod, "Reset the system.");
       this->methods()->addMethod( &nameMethod, "Read out the name of the system.");
       this->methods()->addMethod( &changeP,
                                   "Change a parameter, return the old value.",
	                           "New Value", "The new value for the parameter."); 

       // more additions to follow, see below
     // ...

In the above example, we wish to add 3 class functions to the method interface: reset, getName and changeParameter. This can be done by constructing a Method object with the correct function signature for each such class function. Each Method object is initialised in the constructor with a name ("reset"), a pointer to the class function (&MyTask::reset) and a pointer to the class object (this). This setup allows the method objects resetMethod, nameMethod and paramMethod to be invoked just like one would call the functions directly.

After the method objects are constructed, we add methods to the method interface using the addMethod() function. The addMethod() function requires a a method object (&resetMethod), a description ("Reset the system.") and a name, description pair for each argument (such as in changeParameter).

Using this mechanism, any method of any class can be added to a task's method interface.

3.6.1. Invoking Methods in C++

In order to easily invoke a task's methods from a C++ program, only only needs a pointer to a TaskContext object, for example using the 'getPeer()' class function.

  // create a method:
  TaskContext* a_task_ptr;
  Method<void(void)> my_reset_meth 
       = a_task_ptr->methods()->getMethod<void(void)>("reset");

  // Call 'reset' of a_task:

Methods can also be given arguments and collect return values. Both constant arguments and variable arguments are supported.

  // used to hold the return value:
  string name;
  Method<string(void)> name_meth = 

  // Call 'name' of a_task:
  name = name_meth(); 

  cout << "Name was: " << name << endl; 

  // hold return value.
  double oldvalue;
  Method<double(double)> mychange_1 =

  // Call 'changeParameter' of a_task with argument '1.0'
  oldvalue = mychange_1( 1.0 );
  // oldvalue now contains previous value.

Up to 4 arguments can be given. If the signature was not correct, the method invocation will be ignored. One can check validity of a method object with the 'ready()' function:

  Method<double(double)> mychange_1 = ...;
  assert( mychange_1.ready() );

3.6.2. Invoking Methods in Scripts

To invoke methods from a script, one can then write :

  do ATask.changeP( 0.1 )
  // or :
  set result = ATask.changeP( 0.1 ) // store return value 

3.7. Method Argument and Return Types

The arguments can be of any class type and type qualifier (const, &, *,...). However, to be compatible with the Orocos Program Parser variables, it is best to follow the following guidelines :

Table 2.1. Method Return & Argument Types

C++ TypeIn C++ functions passed byMaps to Parser variable type
Primitive C types : double, int, bool, charvalue (no const, no reference )double, int, bool, char
C++ Container types : std::string, std::vector<double>const &string, array
Orocos Fixed Container types : RTT::Double6D, KDL::[Frame | Rotation | Twist | ... ]const &double6d, frame, rotation, twist, ...

Summarised, every non-class argument is best passed by value, and every class type is best passed by const reference. The parser does handle references (&) in the arguments or return type as well.

3.8. The Attributes and Properties Interface


A task's attributes and properties are intended to configure and tune a task with certain values. Properties have the advantage of being writable to an XML format, hence can store 'persistent' state. For example, a control parameter. Attributes are lightweight values which can be read and written during runtime, for example, the current measured temperature.

A TaskContext may have any number of attributes or properties, of any type. They can be used by programs in the TaskContext to get (and set) configuration data. The task allows to store any C++ value type and also knows how to handle Property objects. Attributes are plain variables, while properties can be written to and updated from an XML file.

3.8.1. Adding Task Attributes or Properties

An attribute can be added in the task's interface (AttributeRepository) like this :

  #include <rtt/Property.hpp>
  #include <rtt/Attribute.hpp>

  class MyTask
    : public TaskContext
     Attribute<bool> aflag;
     Attribute<int> max;

     Constant<double> pi;

     Property<std::string> param;
     Property<double> value;
    // ...
    MyTask(std::string name)
      : TaskContext(name),
        param("Param","Param Description","The String"),
	value("Value","Value Description", 1.23 ),
	aflag("aflag", false),
	max( "max", 5 ),
	pi( "pi", 3.14 )
       // other code here...

       this->attributes()->addAttribute( &aflag );
       this->attributes()->addAttribute( &max );
       this->attributes()->addConstant( &pi );

       this->properties()->addProperty( &param );
       this->properties()->addProperty( &value );
     // ...

Which inserts an attribute of type bool and int, name 'aflag' and 'max' and initial value of false and 5 to the task's interface. A constant 'pi' is added as well. The methods return false if an attribute with that name already exists. Adding a Property is also straightforward. The property is added in a PropertyBag.

3.8.2. Accessing Task Attributes or Properties in C++

To get a value from the task, you can use the set() and get() methods :

  bool result = aflag.get();
  assert( result == false );

  param.set("New String");
  assert( param.get() == "New String" );

While another task can access it through the attributes() interface:

  Attribute<bool> the_flag = a_task->attributes()->getAttribute<bool>("aflag");
  assert( the_flag.ready() );

  bool result = the_flag.get();
  assert( result == false );

  Attribute<int> the_max = a_task->attributes()->getAttribute<int>("max");
  assert( the_max.ready() );
  the_max.set( 10 );
  assert( the_max.get() == 10 );

The attributes 'the_flag' and 'the_max' are called 'mirrors' of the original attributes of the task.

3.8.3. Accessing Task Attributes in Scripts

A program script can access the above attributes as in

  // a program in "ATask" does :
  var double pi2 = pi * 2.
  var int    myMax = 3
  set max = myMax

  set Param = "B Value"

  // an external (peer task) program does :
  var double pi2 = ATask.pi * 2.
  var int    myMax = 3
  set ATask.max = myMax	

When trying to assign a value to a constant, the script parser will throw an exception, thus before the program is run. You must always specify the task's name (or 'task') when accessing a task's attribute, this is different from methods and commands, which may omit the task's name if the program is running within the task.


The same restrictions of Section 3.7, “Method Argument and Return Types” hold for the attribute types, when you want to access them from program scripts.

3.8.4. Storing and Loading Task Properties

See Section 6.1, “Task Property Configuration” for storing and loading the Properties to and from files, in order to store a TaskContext's state.

3.9. The Command Interface


A task's commands are intended to be called 'asynchronously', thus sent by the caller to the receiver. Use it to 'reach a goal' in the receiver, typically this takes time to accomplish. Command functions are, in contrast with methods, executed by the receiver.

The command interface is very similar to the Method interface above.

3.9.1. Adding Commands to a TaskContext

To add a command to the Command Interface, one must create Command, objects :

  #include <rtt/Command.hpp>

  class MyTask
    : public TaskContext
     * The first command starts a cycle.
    bool startCycle() { ... }
    bool cycleDone() const { ... }

    Command<bool(void)> cycleCommand;

     * Another command cleans stuff up.
    bool cleanupMess(double f) { ... }
    bool isMessCleaned() const { ... }

    Command<bool(double)> messCommand;

    MyTask(std::string name)
      : TaskContext(name),
                     &MyTask::cycleDone, this),
        messCommand( "cleanup",
                     &MyTask::isMessCleaned, this)
      // ... other startup code here

      this->commands()->addCommand( &cycleCommand,
                                    "Start a new cycle.");
      this->commands()->addCommand( &messCommand,
                                    "Start cleanup operation.",
	                            "cfactor", "A cfactor denoting the thoroughness.");

Commands differ from Methods in that they take an extra function which is called the Completion Condition. It is a function which returns true when the command is done. The command itself also returns a boolean which indicates if it was accepted or not. Reasons to be rejected can be faulty arguments or that the system is not ready to accept a new command.

The Command object requires two member pointers instead of one, which must both return a 'bool'. The first one is the command function that does the actual work, and the completion condition is a function having :

  • exactly the same arguments as the command,

  • OR only the first argument of the command,

  • OR no arguments at all.

Analogous to addMethod(), addCommand adds the Command objects to the TaskContext interface and also requires a string describing the command, and two strings giving a name and description for every argument.

3.9.2. Invoking Commands in C++

Once a command is added to a TaskContext's interface, other tasks can make use of that command.

The Command class can be used to invoke commands as well. You can get such object from a task's interface:

  Command<bool(void)> mycom 
     = a_task.commands()->getCommand<bool(void)>("startCycle");
  // check if the command is ok:
  assert( mycom.ready() );

  // Send 'startCycle' to a_task (asynchronous).
  bool result = mycom();
  // next, check its status:
  bool accepted = mycom.accepted(); // accepted by execution engine?
  bool valid = mycom.valid();       // command was valid (well-formed)?
  bool done = mycom.done();         // command was done?

Such commands can also be given arguments. Both constant arguments and variable arguments are supported:

  // get a command:
  Command<bool(double)> mycleanup_1 =

  // Send 'cleanup' to a_task with argument '1.0'
  bool result_1 = mycleanup_1( 1.0 );

  bool d_arg = 5.0;
  // Send 'cleanup' to a_task, reads contents of d_arg.
  bool result_2 = mycleanup_1(d_arg);

The current implementation supports up to 4 arguments. Since the use of 'structs' is allowed, this is enough for most applications.

3.9.3. Invoking Commands from Scripts

The above lets you write in a program script :

  do startCycle()
  do cleanup( 0.1 )	

when the program is loaded in a_task.

Commands returning false will propagate that error to the program or function calling that command, which will cause the program to enter an error state, ie it stops its execution.


The same restrictions of Section 3.7, “Method Argument and Return Types” hold for the command and condition types, when you want to access them from program scripts.

3.10. The Event Interface


A task's events are intended to be 'emitted', thus published by the task to subscribers. Use it to 'notify' interested parties of a change in the system.

A task may register its events in its interface in order to be used by its state machines and other tasks as well. Events are defined and explained in the Orocos CoreLib Reference Manual.

3.10.1. Adding Events

Events can be easily added to a task's interface, much like methods are:

  #include <rtt/Event.hpp>

  class MyTask
    : public TaskContext
    // An event with a bool argument:
    Event< void(bool) > turnSwitch;
    // An event with three arguments:
    Event< bool(double, double, double) > moveAxis;
    MyTask(std::string name)
      : TaskContext(name),
        turnSwitch( "turnSwitch" ),
	moveAxis( "move" )
      // ... other startup code here
      // add it to the task's interface:
      this->events()->addEvent( &turnSwitch, 
                                "Turn switch description", 
                                "d","Direction" ); 
      this->events()->addEvent( &moveAxis,
                                "x","X axis position",
				"y","Y axis position",
				"z","Z axis direction");

An Event object has the signature ('void(bool)') of the 'callback function' it will call when the event is 'emitted' (or 'fired'). The object is initialised with a name ("turnSwitch") and added to the interface ('addEvent').

3.10.2. Emitting Events in C++

Once events are added, they can be emitted using the Event object.

  Event< bool(double, double, double) > move_event 
    =>getEvent( "move" );
  assert( move_event.ready() );

  // emit the event 'move' with given args:
  move_event(1.0, 2.0, 3.0);

  // or with variable arguments:
  double a = 0.3, b = 0.2, c = 0.1;
  move_event(a, b, c); 

3.10.3. Reacting to Events in C++

Analogous to emitting an event, one can also react to an event in C++, using the Event interface. Event connections can be accessed through the Handle object. The first example shows how to setup a synchronous connection to the event of the previous examples:

   #include <boost/bind.hpp> 
   * Example: Connect a class method to an Event.  
  class Reactor 
     bool react_callback(double a1, double a2, double a3) { 
        // use a1,a2, a3 
	return false; // return value is ignored.

   * Example: Connect a 'C' function to an Event.
  bool foo_callback( double a1, double a2, double a3 ) {
      // use a1, a2, a3
      return false; // ignored.

  // Class callback:
  Reactor r;

  Handle h
                 .callback( &r, &Reactor::react_callback )
  assert( h.ready() );
  h.connect(); // connect to event "move"

  move_event(1.0, 2.0, 3.0); // see previous example.

  // now Reactor::callback() was called.

  h.disconnect(); // disconnect again.

  // 'C' Function callback:
  h =>setupConnection("move")
                 .callback( &foo_callback )

  move_event(4.0, 5.0, 6.0)

  // now foo_callback is called with arguments.	

Using the boost::bind function is not yet supported in this interface. You must provide the object and function separately in callback().

Analogous to the event example in the CoreLib Reference Manual, a class is made to react to the event. A connection is setup between the "move" event and the react_callback function of "r". The connection can be controlled using the handle to connect or disconnect the reaction to events. When connect() is called, every event invocation will call react_callback() with the given arguments. Using a 'C' function works analogous as shown above.

A second example continues, but uses an asynchronous connection. First a new task (b_task) is created which will handle the event asynchronously. During setup, the EventProcessor of b_task's Execution Engine is used to process the event.

  TaskContext b_task("BTask");
  PeriodicActivity ptask_b(5, 0.1); // priority, period &b_task );

  Handle h3 
                            .callback(&r, &react_callback,
                                      b_task.engine()->events() ).handle();
  assert( h3.ready() );

  h3.connect(); // connect asynchronously to event "move"

  move_event.emit(); // see previous example.

  // wait a bit...

  // now react_callback() was called from within b_task's execution engine.

Note that after passing the object and function, the EventProcessor of b_task is added in the callback method, such that the callback is executed in b_task's thread.

3.10.4. Using Events from Scripts

Events are as easy to use as methods (above) from within scripts, using the keyword do:

  do ATask.move( 1.0, 2.0, 3.0 )

It is also possible to react to events from within a state machine in order to change state. We refer to the Program Parser Manual for syntax and examples.

4. Connecting TaskContexts

A Real-Time system contains multiple concurrent tasks which must communicate to each other. TaskContext can be connected to each other such that they can communicate Real-Time data.

4.1. Setting up the Execution Flow

The addPeer and connectPeers functions are used to connect TaskContexts and allow them to use each other's interface. The connectPorts funtion sets up the data flow between tasks.

We call connected TaskContexts "Peers" as there is no fixed hierarchy. A connection from one TaskContext to its Peer can be uni- or bi-directional. In a uni-directional connection (addPeer ), only one peer can use the interface of the other, while in a bi-directional connection (connectPeers), both can use each others interface. This allows to build strictly hierarchical topological networks as well as complete flat or circular networks or any kind of mixed network.

Peers are connected as such (hasPeer takes a string argument ):

  // bi-directional :
  connectPeers( &a_task, &b_task );
  assert( a_task.hasPeer( &b_task.getName() ) 
          & b_task.hasPeer( &a_task.getName() ) );
  // uni-directional :
  a_task.addPeer( &c_task );
  assert( a_task.hasPeer( &c_task.getName() ) 
          & ! c_task.hasPeer( &a_task.getName() ) );

  // Access the interface of a Peer:
  Method<bool(void) m = a_task.getPeer( "CTask" )->methods()->getMethod<bool(void)>("aMethod");
  // etc. See interface usage in previous sections.

Both connectPeers and addPeer allow scripts or C++ code to use the interface of a connected Peer. connectPeers does this connection in both directions.

From within a program script, peers can be accessed by merely prefixing their name to the member you want to access. A program within "ATask" could access its peers as such :

  var bool result = CTask.aMethod() 

The peer connection graph can be traversed at arbitrary depth. Thus you can access your peer's peers.

4.2. Setting up the Data Flow

Data Flow between TaskContexts is setup by using connectPorts. The direction of the data flow is imposed by the read/write direction of the ports. The connectPorts(TaskContext* A, TaskContext* B) function creates a connection between TaskContext ports when both ports have the same name and type. It will never disconnect existing connections and only tries to add ports to existing connections or create new connections.

Before calling connectPorts, one may connect individual ports using a_port.connectTo(&b_port); when complexer data flow networks need to be formed.

Example 2.1. TaskContext Data Flow Topology Example

This diagram shows some possible topologies. Four tasks, "A", "B", "C" and "D" have each a port "MyData" and a port "MyData2". The example demonstrates that connections are always made from writer (sender) to reader (receiver).

Example data flow networks.

The first network has two writers and two readers for "MyData". It can be formed starting from "A" and adding "B","C" and "D" as peers of "A" respectively. Since the network started from "A" all peers share the same connection. The same network could have been formed starting from "B". The second diagram connects "A" to "C" and then "B" to "D". Two connections are now made and if the application tries to connect "B" to "C", this will fail since the "MyData" Port of "C" already participates in a connection.

The third network has one writer and three readers for "MyData2". It can now only be formed starting from "D" and adding "A","B" and "C" as peers to "D". Combining both network one and three is possible by merely invoking all the 'addPeer' methods in the correct order.

connectPorts tries to create connections in both directions. If a task's Port already has a connection, any task with compatible, unconnected ports will be added to that connection. For example, if "a_task" and "b_task" exchange a Data type "Data_X", and "c_task" reads "Data_X", the connectPorts will forward "Data_X" to "c_task" as well.

4.3. Disconnecting Tasks

Tasks can be disconnected from a network by invoking disconnect() on that task. It will inform all its peers that it has left the network and disconnect all its ports. This does not mean that all data flow connections are deleted. As long as one task's port still participates in a connection, the connections exist. When the last port disconnects, the data flow connection is cleaned up as well.

Example 2.2. TaskContext Peer Disconnection Example

(1) shows what would happen if tasks "A" and "B" are disconnected from the network. (2) shows what would happen if the connection itself is disconnected.

Disconnecting tasks: one can disconnect a whole task or disconnect only a port or connection of a task.

When A.disconnect() is called (1), it removes its participation from the "MyData" connection. The same happens for B.disconnect(). "C" and "D" read then from a connection which has no more writers. Adding "A" again to the network would make "A" again a writer of "MyData". If both "C" and "D" call disconnect as well, the "MyData" connection is cleaned up.

  assert( !a_task.hasPeer( &b_task.getName() ) 
          && !b_task.hasPeer( &a_task.getName() );

  assert( !c_task.hasPeer( &b_task.getName() ) 
          && ! d_task.hasPeer( &b_task.getName() );

Data Flow connections can be disconnected (2) as well, in which case all ports are disconnected.

  ConnectionInterface::shared_ptr con = a_task.ports()->getPort("MyData")->connection();
  if (con)

  assert( !a_task.ports()->getPort("MyData").connected() );
  assert( !b_task.ports()->getPort("MyData").connected() );
  assert( !c_task.ports()->getPort("MyData").connected() );
  assert( !d_task.ports()->getPort("MyData").connected() ); 

5. Deploying Components

An Orocos component can be used in both embedded (<1MB RAM) or big systems (128MB RAM), depending on how it is created or used. This is called Component Deployment as the target receives one or more component implementations. The components must be adapted as such that they fit the target.

5.1. Overview

Figure 2.6, “ Component Deployment Levels ” shows the distinction between the three levels of Component Deployment.

Figure 2.6.  Component Deployment Levels

Component Deployment Levels

Three levels of using or creating Components can be accomplished in Orocos: Not distributed, embedded distributed and fully distributed.

If your application will not use distributed components and requires a very small footprint, the TaskCore can be used. The Orocos primitives apear directly in the interface and are called upon in a hard-coded way.

If you application requires a small footprint and distributed components, the C++ Interface of the TaskContext can be used in combination with a Distribution Library which does the network translation. It handles a predefined set of data types (mostly the 'C' types) and needs to be adapted if other data types need to be supported.

If footprint is of no concern to your application and you want to distribute any component completely transparantly, the TaskContext can be used in combination with a Remoting Library which does the network translation. A CORBA implementation of such a library is being developed on. It is a write-once, use-many implementation, which can pick up user defined types, without requiring modifications. It uses the Orocos Type System to manage user defined types.

5.2. Embedded TaskCore Deployment

A TaskCore is nothing more than a place holder for the Execution Engine and application code functions (startup(), update() and shutdown() ). The Component interface is built up by placing the Orocos primitives as public class members in a TaskCore subclass. Each component that wants to use this TaskCore must get a 'hard coded' pointer to it (or the interface it implements) and invoke the command, method etc. Since Orocos is by no means informed of the TaskCore's interface, it can not distribute a TaskCore.

5.3. Embedded TaskContext Deployment: C++ Interface

Instead of putting the Orocos primitives in the public interface of a subclass of TaskCore, one can subclass a TaskContext and register the primitives to the C++ Interface. This is a reduced interface of the TaskContext, which allows distribution by the use of a Distribution Library.


The code presented is for commands, but can be equally applied for methds by using methods()->addMethod( & method ) for events and for each other Orocos primitive.

The process goes as such: A component inherits from TaskContext and has some Orocos primitives as class members. Instead of calling:

  commands()->addCommand(&com, "Description", "Arg1","Arg1 Description",...);

and providing a description for the primitive as well as each argument, one writes:

  commands()->addCommand( &com );

This is no more than a pointer registration, but already allows all C++ code to use the added primitive.

In order to access the interface of such a Component, the user code may use:


In order to distribute this component, an implementation of the Distribution Library is required. The specification of this library, and the application setup is in left to another design document.

5.4. Full TaskContext Deployment: Dynamic Interface

In case you are building your components as instructed in this manual, your component is ready for distribution as-is, given a Remoting library is used. The Orocos CORBA package implements such a Remoting library.

5.5. Putting it together

Using the three levels of deployment in one application is possible as well. To save space or execution efficiency, one can use TaskCores to implement local (hidden) functionality and export publicly visible interface using a Taskcontext. Figure 2.7, “ Example Component Deployment. ” is an small example of a TaskContext which uses two TaskCores to delegate work to. The Execution Engines may run in one or multiple threads.

Figure 2.7.  Example Component Deployment.

Example Component Deployment.

6. Using Tasks

This section elaborates on the interface all Task Contexts have from a 'Task user' perspective.

6.1. Task Property Configuration

As was seen in Section 3.8, “The Attributes and Properties Interface”, Property objects can be added to a task's interface. To read and write properties from or to files, you can use the TaskContext class' methods. It creates or reads files in the XML Component Property Format such that it is human readable and modifiable.

  // ...
  TaskContext* a_task = ...
  a_task->readProperties( "PropertyFile.cpf" );
  // ...
  a_task->writeProperties( "PropertyFile.cpf" ); 

Where readProperties() reads the file and updates the task's properties and writeProperties() updates the given file with the properties of the task. It is allowed to share a single file with multiple tasks or update the task's properties from multiple files.

6.2. Task Scripts

Orocos supports two types of scripts:

  • An Orocos Program Script (ops) contains a Real-Time functional program which calls methods and sends commands to tasks, depending on classical functional logic.

  • An Orocos State machine Description (osd) script contains a Real-Time (hierarchical) state machine which dictates which program script snippets are executed upon which event.

Both are loaded at runtime into a task. The scripts are parsed to an object tree, which can then be executed by the ExecutionEngine of a task.

6.2.1. Program Scripts

Program can be finely controlled once loaded in the ProgramProcessor, which is part of the Execution Engine. A program can be paused, it's variables inspected and reset while it is loaded in the Processor. A simple program script can look like :

  program foo
    var int i = 1
    var double j = 2.0
    do changeParameter(i,j)

Any number of programs may be listed in a file.

Orocos Programs are loaded as such into a TaskContext :

  TaskContext* a_task = ...

  a_task->scripting()->loadPrograms( "ProgramBar.ops" ); 

When the Program is loaded in the Task Context, it can also be controlled from other scripts or a TaskBrowser. Assuming you have loaded a Program with the name 'foo', the following commands are available :


While you also can inspect its status :

You can also inspect and change the variables of a loaded program, but as in any application, this should only be done for debugging purposes.

  set = 3
  var double oldj =

Program scripts can also be controlled in C++. Take a look at the ProgramInterface class reference for more program related functions. One can get a pointer to a program by calling:

  ProgramInterface* foo = this->engine()->getProgram("foo");
  if (foo != 0) {
    bool result = foo->start(); // try to start the program !
    if (result == false) {
       // Program could not be started.
       // Execution Engine not running ?

6.2.2. State Machines

Hierarchical state machines are modelled in Orocos with the StateMachine class. They are like programs in that they can call a peer task's members, but the calls are grouped in a state and only executed when the state machine is in that state. This section limits to showing how an Orocos State Description (osd) script can be loaded in a Generic Task Context.

  TaskContext* a_task = ...

  a_task->scripting()->loadStateMachines( "StateMachineBar.osd" ); 

When the State Machine is loaded in the Task Context, it can also be controlled from your scripts or TaskBrowser. Assuming you have instantiated a State Machine with the name 'machine', the following commands are available :

  do states.machine.activate()
  do states.machine.start()
  do states.machine.pause()
  do states.machine.step()
  do states.machine.stop()
  do states.machine.deactivate()
  do states.machine.reset()
  do states.machine.reactive()
  do states.machine.automatic() // identical to start()
  do states.machine.requestState("StateName")

As with programs, you can inspect and change the variables of a loaded StateMachine.

  set programs.machine.myParam = ...

The Scripting Manual goes in great detail on how to construct and control State Machines.

7. Advanced Techniques

If you master the above methods of setting up tasks, this section gives some advanced uses for integrating your existing application framework in Orocos Tasks.

7.1. Using the TaskContext

To help users in setting up quickly a TaskContext, the TaskContext class has been made available which adds some standard methods and commands to its interface which are common to many tasks. It supports loading Programs and StateMachines, saving Properties to disk and reading them back in and stopping and starting the Task. You can download an introduction to setting up TaskContexts which uses this class from the download page.

7.2. Wrapping Methods in Functions

Methods are always executed in the thread of the caller. If a method does non-real-time operations, like writing data to disk, it should not be called by a real-time thread. However, if the thread which owns the method is itself not real-time, it can execute the method as a command in its own thread. This can easily be accomplished by writing a wrapper function ( or alternatively, register the method as a command too ).

  export function domethod( int arg ) {
     do mymethod( arg )

Load this function with the ProgramLoader in the TaskContext having 'mymethod', and hard real-time tasks can instruct it to execute that method, without jeopardizing their own real-time behaviour.

7.3. Waiting for Something : Synchronisation

When tasks need to synchronise, you have a wide range of options to use.

7.3.1. Waiting in States

A (sub-)State Machine can pause itself and an extra function in the task's interface can provide the key to progress to another state. First the StateMachine is loaded in an .osd file :

  StateMachine X {
     // ...
     state y {
        entry {
           // pause myself, no transitions are checked.
           do this.pause()
        transitions {
	   // guard this transition.
           if checkSomeCondition() then
              select z
     state z {
       // ...

  RootMachine X x

Then, load an ops file which contains :

  export function progress() {
    // Check if we may progress :
    if this.states.x.inState("y") then {
        // continue :
        do this.states.x.start()
        // OR try single transition :
        do this.states.x.step()

A peer task then calls progress() which in turn checks if the function is applicable. But even then, the responsibility of the transition lies within the State Machine.

Off course, the example can be simplified by setting/ resetting a boolean flag between function and State Machine.

  StateMachine X {
     // ...
     state y {
        transitions {
           if progressflag == true then
                select z
     state z {
       // ...

  RootMachine X x

Then, load an ops file which contains :

  export function progress() {
    // Check if we may progress :
    if this.states.x.inState("y") then {
          set progressflag = true

When the user or another program calls the progress() command, the flag will be set.

7.3.2. Requesting States

A State Machine can be used such that it waits for state change requests instead of discovering itself to which state it makes a transition. This requires the State Machine to run in another mode, the requestState mode ( as opposed to the automatic mode, which is entered by start() ).

  StateMachine X {
     // ...
     state y {
        entry {
	   // ...
        transitions {
	   // guard this transition.
           if checkSomeCondition() then
              select z
	   // always good to go to states :
	   select ok_1
           select ok_2
     state z {
       // ...
     state ok_1 {
       // ...
     state ok_2 {
       // ...

  RootMachine X x

Then, load an ops file which contains :

  export function progress() {
       // request to enter anther state :
       do this.states.x.requestState("z")
  export function progress_Ok() {
       // this will succeed always from state 'x' :
       do this.states.x.requestState("ok1")

This command will fail if the transition is not possible ( for example, the state machine is not in state y, or checkSomeCondition() was not true ), otherwise, the state machine will make the transition and the command succeeds and completes when the z state is fully entered (it's init program completed).

To merely request that a state is handled, one can call requestState on the current state :

  export function handleState() {
       // request to handle current state :
       do this.states.x.requestState( this.states.x.getState() )

To request to go to the next possible state (or call handle if none) and then wait again for requests, use 'step()' :

  export function evaluate() {
       // request go to the next state and wait :
       do this.states.x.step()

Note that if the StateMachine happened to be paused, step() would only progress one single statement. To check if the StateMachine is waiting for requests, use the 'inRequest()' method :

  export function progress() {
       if ( this.states.x.inRequest() ) {
           // ... it's waiting
       } else {
          // was not waiting, possibly running, paused or non active

All these methods can of course also be called from parent to child State Machine, or across tasks.

7.4. Polymorphism : Task Interfaces

Most projects have define their own task interfaces in C++. Assume you have a class with the following interface :

  class DeviceInterface
     * Set/Get a parameter. Returns false if parameter is read-only.
    virtual bool setParameter(int parnr, double value) = 0;
    virtual double getParameter(int parnr) const = 0;

     * Get the newest data.
     * Return false on error.
    virtual bool updateData() = 0;
    virtual bool updated() const = 0;

     * Get Errors if any.
    virtual int getError() const = 0;

Now suppose you want to do make this interface available, such that program scripts of other tasks can access this interface. Because you have many devices, you surely want all of them to be accessed transparantly from a supervising task. Luckily for you, C++ polymorphism can be transparantly adopted in Orocos TaskContexts. This is how it goes.

7.4.1. Step 1 : Export the interface

We construct a TaskContext, which exports your C++ interface to a task's interface.

  #include <rtt/TaskContext.hpp>
  #include <rtt/Command.hpp>
  #include <rtt/Method.hpp>
  #include "DeviceInterface.hpp"

  class TaskDeviceInterface
    : public DeviceInterface,
      public TaskContext
        : TaskContext( "DeviceInterface" )

      void setup() 
         // Add Methods :
	                   "Set a device parameter.",
	                   "Parameter", "The number of the parameter.",
	                   "New Value", "The new value for the parameter."); 

	                  "Get a device parameter.",
                          "Parameter", "The number of the parameter.");
	                 "Get device error status.");

         // Add Commands :
                                 "Command data acquisition." );

The above listing just combines all operations which were introduced in the previous sections. Also note that the TaskContext's name is fixed to "DeviceInterface". This is not obligatory though.

7.4.2. Step 2 : Inherit from the new interface

Your DeviceInterface implementations now only need to inherit from TaskDeviceInterface to instantiate a Device TaskContext :

  #include "TaskDeviceInterface.hpp"

  class MyDevice_1 
    : public TaskDeviceInterface

    bool setParameter(int parnr, double value) {
      // ...
    double getParameter(int parnr) const {      // ...
    // etc.

7.4.3. Step 3 : Add the task to other tasks

The new TaskContext can now be added to other tasks. If needed, an alias can be given such that the peer task knows this task under another name. This allows the user to access different incarnations of the same interface from a task.

	  // now add it to the supervising task :
  MyDevice_1 mydev;
  supervisor.addPeer( &mydev, "device" );

From now on, the "supervisor" task will be able to access "device". If the implementation changes, the same interface can be reused whithout changing the programs in the supervisor.

A big warning needs to be issued though : if you change a peer at runtime (after parsing programs), you need to reload all the programs, functions, state contexts which use that peer so that they reference the new peer and its C++ implementation.

7.4.4. Step 4 : Use the task's interface

To make the example complete, here is an example script which could run in the supervisor task :

  program ControlDevice
     const int par1 = 0
     const int par2 = 1
     do device.setParameter(par1, supervisor.par1 )
     do device.setParameter(par2, supervisor.par2 )

     while ( device.getError() == 0 ) 
	if ( this.updateDevice("device") == true )
           do device.updateData() until {
	        if done || ( device.getError() != 0 ) then
     do this.handleError("device", device.getError() )

To start this program from the TaskBrowser, browse to supervisor and type the command :


When the program "ControlDevice" is started, it initialises some parameters from its own attributes. Next, the program goes into a loop and sends updateData commands to the device as long as underlying supervisor (ie "this") logic requests an update and no error is reported. This code guarantees that no two updateData commands will intervene each other since the program waits for the commands completion or error. When the device returns an error, the supervisor can then handle the error of the device and restart the program if needed.

The advantages of this program over classical C/C++ functions are :

  • If any error occurs (ie a command or method returns false), the program stops and other programs or state contexts can detect this and take apropriate action.

  • The "device.updateData()" call waits for completion of the remote command, but can be given other completion or error conditions to watch for.

  • While the program waits for updateData() to complete, it does not block other programs, etc within the same TaskContext and thread.

  • There is no need for additional synchronisation primitives between the supervisor and the device since the commands are queued and executed in the thread of the device, which leads to :

    • The command is executed at the priority of the device's thread, and not the supervisor's priority.

    • The command can never corrupt data of the device's thread, since it is serialised(executed after) with the programs running in that thread.

Chapter 3. Orocos Scripting Reference


This document describes the Orocos Scripting system.

1. Introduction

The Orocos Scripting language allows users of the Orocos system to write programs and state machines controlling the system in a user-friendly real-time script language. The advantage of scripting is that it is easily extendible and does not need recompilation of the main program.

2. General Scripting Concepts

Before starting to explain Program Syntax, it is necessary to explain some general concepts that are used throughout the program syntax.


Various sorts of comments are supported in the syntax. Here is a small listing showing the various syntaxes:

  # A perl-style comment, starting at a '#', and running until
  # the end of the line.
  // A C++/Java style comment, starting at '//', and running
  // until the end of the line.
  /* A C-style comment, starting at '/*', and running until
     the first closing */ /* Nesting is not allowed, that's
     why I have to start a new comment here :-) 

Whitespace is in general ignored, except for the fact that it is used to separate tokens.

2.2. Identifiers

Identifiers are names that the user can assign to variables, constants, aliases, labels. The same identifier can only be used once, except that for labels you can use an identifier that has already been used as a variable, constant or alias. However, this is generally a bad idea, and you shouldn't do it.

Some words cannot be used as identifiers, because they are reserved by the Orocos Scripting Framework, either for current use, or for future expansions. These are called keywords. The current list of reserved keywords is included here:


These, and all variations on the (upper- or lower-) case of each of the letters are reserved, and cannot be used as identifiers.

2.3. Expressions

Expressions are a general concept used throughout the Parser system. Expressions represent values that can be calculated at runtime (like a+b). They can be used as arguments to functions, conditions and whatmore. Expressions implicitly are of a certain type, and the Parser system does strong type-checking. Expressions can be constructed in various ways, that are described below...

2.3.1. Literals

Literal values of various types are supported: string, int, double, bool. Boolean literals are either the word "true" or the word "false". Integer literals are normal, positive or negative integers. Double literals are C/C++ style double-precision floating point literals. The only difference is that in order for the Parser to be able to see the difference with integers, we require a dot to be present. String literals are surrounded by double quotes, and can contain all the normal C/C++ style escaped characters. Here are some examples:

  // a string with some escaped letters:
  "\"OROCOS rocks, \" my mother said..."
  // a normal integer
  // a double literal
  // and another one..

2.3.2. Constants, Variables and Aliases

Constants, variables and aliases allow you to work with data in an easier way. A constant is a name which is assigned a value at parse time, and keeps that value throughout the rest of the program. A variable gets its value assigned at runtime and can be changed at other places in the program. An alias does not carry a value, it is defined with an expression, for which it acts as an alias or an abbreviation during the rest of the program. All of them can always be used as expressions. Here is some code showing how to use them.

  // define a variable of type int, called counter,
  // and give it the initial value 0.
  var int counter = 0
  // add 1 to the counter variable
  set counter = counter + 1
  // make the name "counterPlusOne" an alias for the
  // expression counter + 1.  After this, using
  // counterPlusOne is completely equivalent to writing
  // counter + 1
  alias int counterPlusOne = counter + 1
  // you can assign an arbitrarily complex expression
  // to an alias
  alias int reallycomplexalias = ( ( counter + 8 ) / 3 )*robot.position

  // define a constant of type double, with name "pi"
  const double pi = 3.14159265358979
  const double pi2 = 2*pi       // ok, pi2 is 6.28...
  const int turn = counter * pi // warning ! turn will be 0 !

  // define a constant at _parse-time_ !
  const totalParams = table.getNbOfParams()

Variables, constants and aliases are defined for the following types: bool, int, double, string and array. The Orocos Toolkit System allows any application or library to extend these types.

2.3.3. Strings and Arrays

For convenience, two variable size types have been added to the parser : string and array. They are special because their contents have variable size. For example a string can be empty or contain 10 characters. The same holds for an array, which contains double's. They are mapped on std::string and std::vector<double>. To access them safely from a task method or command, you need to to pass them by const reference : const std::string& s, const std::vector<double>& v.

Container types can be used in two ways : with a predefined capacity (ie the possibility to hold N items), or with a free capacity, where capacity is expanded as there is need for it. The former way is necessary for real-time programs, the latter can only be used in non real-time tasks, since it may cause a memory allocation when capacity limits are exceeded. The following table lists all available constructors:

Table 3.1. array and string constructors

Constructor SyntaxReal-Time InitialisingNotes
var string x = string()
var string x
Creates an empty string. (std::string)
var string x = string("Hello World")
var string x("Hello World")
Creates a string with contents "Hello World".
var array x = array()
var array x
Creates an empty array. (std::vector<double>)
var array x = array(10)
var array x(10)
Creates an array with 10 elements, all equal to 0.0.
var array x = array(10, 3.0)
var array x(10, 3.0)
Creates an array with 10 elements, all equal to 3.0.
var array x = array(1.0, 2.0, 3.0)
var array x(1.0, 2.0, 3.0)
Creates an array with 3 elements: {1.0, 2.0, 3.0}. Any number of arguments may be given.


The 'Constructor Syntax' syntax leads to not real-time scripts ! See the examples below.

Example 3.1. string and array creation

  // A free string and free array :
  // applestring is expanded to contain 6 characters (Non real-time!)
  var string applestring = "apples"

  // values is expanded to contain 15 elements (Non real-time!)
  var array  values      = array(15)         

  // A fixed string and fixed array :
  var string fixstring(10)  // may contain a string of maximum 10 characters
  set fixstring  = applestring   // ok, enough capacity
  set fixstring  = "0123456789x" // runtime program error, not enough room.

  var array  fixvalues(10)  // fixvalues may never contain more than 10 elements
  var array  morevalues(20) // arrays are initialised with n doubles of value 0.0 

  set fixvalues  = morevalues  // will cause program error
  set morevalues = fixvalues   // ok, morevalues has enough capacity, now contains 10 doubles

  set fixvalues  = morevalues  // ok, since morevalues only contains 10 items.

  set values     = array(20)   // expand values to contain 20 doubles. (Non real-time!) 

  var array list(1.0, 2.0, 3.0, 4.0) // list contains {1.0, 2.0, 3.0, 4.0}
  var array biglist;                 // creates an empty array
  set biglist = list           // 'biglist' is now equal to 'list' (Non real-time!)

As the example above demonstrates, a fixed string or array may only be assigned from another string or array with equal or less elements, while a free string or array may be assigned any number of elements.


The 'size' value given upon construction (array(10) or string(17)) must be a legal expression at parse time and is only evaluated once. The safest method is using a literal integer ( i.e. (10) like in the examples ), but if you create a Task constant or variable which holds an integer, you can also use it as in :

  var array example( 5 * numberOfItems )

The expression may not contain any program variables, these will all be zero upon parse time ! The following example is a common mistake also :

  set numberOfItems = 10
  var array example( 5 * numberOfItems )

Which will not lead to '50', but to '5 times the value of numberOfItems, being still zero, when the program is parsed.

Another property of container types is that you can index (use []) their contents. The index may be any expression that return an int.

  // ... continued
  // Set an item of a container :
  for (int i=0; i < 20; set i = i+1)
       set values[i] = 1.0*i

  // Get an item of a container :
  var double sum
  for (int i=0; i < 20; set i = i+1)
       set sum = sum + values[i]  

If an assignment tries to set an item out of range, the command will fail, if you try to read an item out of range, the result will return 0.0, or for strings, the null character.

2.3.4. Operators

Expressions can be combined using the C-style operators that you are already familiar with if you have ever programmed in C, C++ or Java. All operators are supported, except for the if-then-else operator ("a?b:c"), and the precedence is the same as the one used in C, C++, Java and similar languages. In general all that you would expect, is present.

2.3.5. The '.' Operator

Some value types, like array and string in the Parser framework are actually containing values or useful information themselves. For accessing these values, a value type can have a 'dot' operator which allows you to read-only contents of the container :

  var string s1 = "abcdef"

  // retrieve size and capacity of a string :
  var int size = s1.size()
  var int cap  = s1.capacity()

  var array a1( 10 )
  var array a2(20) = a1

  // retrieve size and capacity of a array :
  var int size = a2.size()      // 10
  var int cap  = a2.capacity()  // 20

2.4. Parsing and Loading Programs

Before we go on describing the details of the programs syntax, we show how you can load a program in your Real-Time Task.

You have constructed a TaskContext which has some methods and is connected to its Peer TaskContexts. The program script programs.ops contains a program with the name "progname". Parsing the program is then straightforward :

  #include <rtt/PeriodicActivity.hpp>
  #include <rtt/TaskContext.hpp>

  using namespace RTT;

  TaskContext   tc;
  PeriodicActivity ptask(5, 0.01, tc.engine() );

  // Watch Logger output for errors :

  // start the task :

  // start a program :

The loader will load all programs and functions into 'tc'. Next we start the task's execution engine and finally, the program "progname" is started. Programs can also be started from within other scripts.

3. Orocos Program Scripts

3.1. Program Execution Semantics

An Orocos program script is a list of statements, quite similar to a C program. Programs can call C/C++ functions and functions can be loaded into the system, such that other programs can call them. Program scripts are executed by the Execution Engine.

In general, program statements are executed immediately one after the other. However, when the program needs to wait for a result, the Execution Engine temporarily postpones program execution and will try again in the next execution period. This happens typically when the statement was a Task Command. Task Methods and expressions on the other hand typically do not impose a wait, and thus are executed immediately after each other.

3.2. Program Syntax

3.2.1. program

A program is formed like this:

  program progname {
    // an arbitrary number of statements

The statements are executed in order, starting at the first and following the logical execution path imposed by your program's structure. If any of the statements causes a run-time error, the Program Processor will put the program in the error state and stop executing it. It is the task of other logic (like state machines, see below) to detect such failures.

3.2.2. Variable set Statements

A variable set statement is a statement that sets a variable to a certain value. It looks like this:

  set variablename = expression

Variablename is the name of the variable you want to assign to. It should already have been defined. Expression is an expression of the same type as the type of the variable.

3.2.3. The if then else Statement

A Program script can contain if..then..else blocks, very similar to C syntax.

  if condition then statement 
  [ else statement ]
  // or :
  if condition then {
    // ...
  } [ else {
    // ...
  } ]	  

It is thus possible to group statements. Each statement can be another if clause. An else is always referring to the last if, just like in C/C++. If you like, you can also write parentheses around the condition. The else statement is optional.

3.2.4. The for Statement

The for statement is almost equal to the C language. The first statement initialises a variable or is empty. The condition contains a boolean expression (use 'true' to simulate an empty condition). The second statement changes a variable or is empty.

  for ( statement; condition; statement )
  // or :
  for ( statement; condition; statement ) {
        // ...

3.2.5. The while Statement

The while statement is another looping primitive in the Orocos script language. A do statement is not ( yet ) implemented

  while condition 
  // or :
  while condition {
      // ...

As with the if statement, you can optionally put parentheses around the condition.

3.2.6. The break Statement

To break out of a while or for loop, the break statement is available. It will break out of the innermost loop, in case of nesting.

  var int i = 0
  while true  {
      set i = i + 1
      if i == 50 then
      // ...

It can be used likewise in a for loop.

3.2.7. Invoking Task Methods

Methods behave like calling C functions. They take arguments and return a value immediately. They can be used in expressions or stand alone :

  // ignore the return value :
  do comp.method( args )
  // this will only work if the method returns a boolean :
  if ( comp.method( args ) ) {
  	    // ...
  // use another method in an expression :
  set data = comp.getResult( args ) * 20. / comp.dataValue 

Methods are executed directly one after the other.


A method returning a boolean result, will cause a run-time program error if it returns false. If this is not wanted, use 'try' instead of 'do'. If the method returns nothing or something else than bool, the result will be ignored in a do statement.

3.2.8. Invoking Task Commands

A command statement is a statement that calls a certain command, and defines some reactions. It looks like:

  do comp.action( args ) until {
    if condition then continue
    if condition2 then call func()
    if condition3 then return

It calls the command "action", on the task "comp", with the comma-separated list of expressions args as the arguments. The Program Processor executes the command once, and then checks where to go next using the "completion clauses" in the until part. If none are true, then it waits another tick, and checks them again..


These if .. then clauses are different from the if/then/else statement later in this text and purely meant to detect alternative end conditions of a command.

A completion clause always looks like

  if condition then continue
  // or
  if condition then call func_name
  // or
  if condition then return  

condition can be any kind of expression, that is of type boolean. One special condition is provided, the keyword "done". Every command has an associated "implicit completion condition", and the condition "done" is equivalent to that condition. You can also combine the "done" condition with other expressions, as if it were a normal boolean expression. "continue" means to go to the next statement, return means to end the current program or function. The "call func_name" statement calls a function and is explained in the next section

If a completion list is left out, then an implicit one is generated. This means that the two following statements are equivalent:

  do comp.action( args )
  // the implicitly generated completion list always looks like
  // "if done then continue"
  do comp.action( args ) until { if done then continue }
Accepting and Rejecting Commands

A command can be accepted or rejected by a task. When it returns false, this is seen as a reject and the program goes into an error state. The user can then stop the program or try to continue the program again, which will lead to a re-issuing of the command, which may lead again to the error state.

Try ... Catch Commands

When a command is rejected ( the C++ method returns false ), the program goes into an error state and waits for user intervention. This can be bypassed by using a try...catch statement. It tries to execute the command, and if it is rejected, the optional catch clause is executed :

  // just try it :
  try comp.action( args )
  // When rejected, execute the catch clause :
  try comp.action( args ) catch { 
      // statements...

You may place completion conditions between try and catch :

  try comp.action( args ) 
  until {
      if comp.evaluate() then continue
  catch { 
      // statements...
  // next statement 

If the command was accepted, the next statement is executed.

Parallel Commands with 'and'

When it is desired to execute commands as one command ( in one time ), they can be combined with an 'and' operator :

  do comp.action1() and comp.action2() and comp.action3()

The implicit completion condition (i.e. 'done') is when all listed actions are done. This can be overridden by defining a completion condition with 'until'.

The 'and' operator can also be used with 'try'. In that case, the catch clause will be executed in case any of the listed commands fails.

3.2.9. Emitting Task Events

Events are called as methods and commands.

  // emitting an event:
  do sometask.eventname( argument1, argument2, ..., argumentN ) 

In this case, the task 'sometask' has an event 'eventname' which takes 'N' arguments. Other tasks subscribed to this event will receive the event synchronously or asynchronously with these arguments. More information about events can be found in the CoreLib manual. This event must be part of the task interface.

3.2.10. function

Statements can be grouped in functions. A function can only call a function which is earlier defined. Thus recursive function calling is not allowed.

  function func_name( int arg1, double arg2 ) {
    // an arbitrary number of statements
  export function func_nameN(bool arg) {
    // ...

A function can have any number of arguments, which are passed by value, but it returns no value. A function can be exported, in which case it becomes a public available command, which will fail if one of its statements fails. Hence, this allows to extend the command interface with exported functions of a task at runtime.

3.2.11. Calling functions

A function can be called by writing :

  do foo(arg)   // see 'exported' functions
  call foo(arg) // local functions

The arguments are passed by value and no return value is possible. If one of the commands of the functions returns error, the calling program goes in error. A function may also be called in a completion clause. If the function returns, the next statement of the calling function or program is executed.

3.2.12. Waiting : The 'nothing' Command

A special command 'nothing' is provided. It is useful to implement statements, where the completion list is really the only useful thing to do. The nothing command's completion condition will pause execution exactly one execution step, it can thus also be inserted between methods to force execution to pause and resume in the next execution period.

3.3. Starting and Stopping Programs from scripts

Once a program is parsed and loaded into the Execution Engine, it can be manipulated from another script. This can be done through the programs subtask of the TaskContext in which the program was loaded. Assume that you loaded "progname" in task "ATask", you can write

  do ATask.programs.progname.start()
  do ATask.programs.progname.pause()
  do ATask.programs.progname.step()
  do ATask.programs.progname.step()
  do ATask.programs.progname.stop()

The first line starts a program. The second line pauses it. The next two lines executes one command each of the program (like stepping in a debugger). The last line stops the program fully (running or paused).

Some basic properties of the program can be inspected likewise :

  var bool res =  ATask.programs.progname.isRunning()
  set res = ATask.programs.progname.inError()
  set res = ATask.programs.progname.isPaused()

which all return a boolean indicating true or false.

4. Orocos State Descriptions : The Real-Time State Machine

4.1. Introduction

A StateMachine is the state machine used in the Orocos system. It contains a collection of states, and each state defines a Program on entry of the state, when it is run and on exit. It also defines all transitions to a next state. Like program scripts, a StateMachine must be loaded in a Task's Execution Engine.

4.2. StateMachine Workings

A StateMachine is composed of a set of states. A running StateMachine is always in exactly one of its states. One time per period, it checks whether it can transition from that state to another state, and if so makes that transition. By default, only one transition can be made in one Execution Engine step.

Besides a list of the possible transitions, every state also keeps record of programs to be executed at certain occasions. There can be up to four (all optional) programs in every state: the entry program ( which will be executed each time the state is entered ), the run program ( which will be executed every time the state is the active state ), the handle program ( which will be executed if no transition succeeds ) and the exit program ( which will be executed when the state is left).

There can be more than one StateMachine. If there are more than one, then every StateMachine keeps working as if it was the only StateMachine available. They separately keep track of their own current state, etc.

A StateMachine can have any number of states. It needs to have exactly one "initial state", which is the state that will be entered when the StateMachine is first activated. There is also exactly one final state, which is automatically entered when the StateMachine is stopped. This means that the transition from any state to the final state must always be meaningful.

A State Machine can run in two modes. They are the automatic mode and the reactive (also 'event' or 'request') mode.

4.2.1. Reactive Mode: State Change Semantics

In order to enter the reactive mode, the State Machine must be 'activated'. When active, two possible causes of state transitions can exist: because an event occured or because a transition was requested.

Figure 3.1. State Change Semantics in Reactive Mode

State Change Semantics in Reactive Mode

A state can list to which Orocos (CoreLib) events it reacts, and under which conditions it will make a transition to another state. A state only reacts to events when its entry program is fully executed (done) and an event may be processed when the run program is executed, thus interrupt the run program. The first event that triggers a transition will 'win' and the state reacts to no more events, executes the event's transition program, then the state's exit program, and finally, the next state is entered and its entry program is executed. The next state now listens for events (if any) to make a transition or just executes its run program.

Another program can request a transition to a particular state as well. When the request arrives, the current state checks its transition conditions and evaluates if a transition to that state is allowed. These conditions are separately listed from the event transitions above. If a transition condition is valid, the exit program of the current state is called, the transition program and then the entry program of the requested state is called and the requested state's run program is executed. If a transition to the current state was requested, only the run program of the current state is executed.

In this mode, it is also possible to request a single transition to the 'best' next state. All transition conditions are evaluated and the first one that succeeds makes a transition to the target state. This mechanism is similar to automatic mode below, but only one transition is made ( or if none, handle is executed ) and then, the state machine waits again. The step() command triggers this behaviour.

4.2.2. Automatic Mode: State Change Semantics

In order to enter automatic mode, the State Machine must be started with the start() command (see later on).


This mechanism is in addition to 'reactive' mode. A state machine in automatic mode still reacts to events.

Figure 3.2. State Change Semantics in Automatic Mode

State Change Semantics in Automatic Mode

The automatic mode additionally actively evaluates guard conditions. Event reaction remains in effect, but is not shown in this diagram.

In automatic mode, after the run program of the current state finishes, the transition table (to other states) of the current state is evaluated. If a transition succeeds, the transition program is executed, then the exit program of the current state is called and then the entry program of the next state is called. If no transition evaluated to true, the handle program (if any) of the current state is called. This goes on until the automatic mode is left, using the pause, stop or reactive command.

4.3. Parsing and Loading StateMachines

Analogous to the Program section, we first show how you can load a StateMachine in your Real-Time Task.

Assume that you have a StateMachine "statename" in a file state-machine.osd. You've read the Orocos Task Infrastructure manual and constructed a TaskContext which has some methods and is connected to its Peer TaskContexts. Parsing the StateMachine is very analogous to parsing Programs:

  #include <rtt/PeriodicActivity.hpp>
  #include <rtt/TaskContext.hpp>

  using namespace RTT;

  TaskContext   tc;
  PeriodicActivity ptask(5, 0.01, tc.engine() );

  tc.scripting()->loadStateMachines( "state-machine.osd" );

  // start the task's processor :

  // activate a state machine :
  // start a state machine (automatic mode) :

The loader loads all instantiated state machines in tc. Next we start the task's Execution Engine. StateMachines have a more complex lifetime than Programs. They need first to be activated, upon which they enter a fixed initial state. When they are started, they enter automatic mode and state transitions to other states can take place. StateMachines can also be manipulated from within other scripts.

4.4. Defining StateMachines

You can think of StateMachines somewhat like C++ classes. You first need to define a type of StateMachine, and you can then instantiate it any number of times afterwards. A StateMachine ( the type ) can have parameters, so every instantiation can work differently based on the parameters it got in its instantiation.

A StateMachine definition looks like this :

Example 3.2. StateMachine Definition Format

  StateMachine MyStateMachineDefinition
    initial state myInit
        // all these programs are optional and can be left out:
        entry {
	    // entry program
	run {
	    // run program
	handle {
	    // handle program
	exit {
	    // exit program
	transitions {
	    // Ordered (conditional) select statements

    final state myExit {
	entry {
	    // put everything in a safe state.
	// leave out empty programs...

	transitions {
	    // ...

    state Waiting {
        // ...

    // ... repeat

  // See Section 4.5, “Instantiating Machines: SubMachines and RootMachines” :
  RootMachine MyStateMachineDefinition MachineInstanceName

A StateMachine definition: a StateMachine can have any number of states. It needs to have exactly one "initial state" ( which is the state that will be entered when the StateMachine is first started ). Within a state, any method is optional, and a state can even be defined empty.

4.4.1. The state Statement

A state machine can have an unlimited number of states. A state contains optionally 4 programs : entry, run, handle, exit. Any one of them is optional, and a state can even conceivably be defined empty.

4.4.2. The entry and exit Statements

When a state is entered for the first time, the entry program is executed. When it is left, the exit program is called. The execution semantics are identical to the program scripts above.

4.4.3. The run Statement

The run program serves to define which activity is done within the state. After the entry program finishes, the run program is immediately started. It may be interrupted by the events that state reacts to. In event mode, the run program is executed once (although it may use an infinite loop to repeatedly execute statements). In automatic mode, when the run program completes, and no transitions to another state can be made (see below) it is started again (in the next execution step).

4.4.4. The handle and transitions Statement

When the run program returns in automatic mode, the state evaluates its transitions to other states. The handle program is called only when no transition can be found to another state. The transitions section defines one or more select state statements. These can be guarded by if...then clauses (the transition conditions):

  // In state XYZ :
  transitions {
    // conditionally select the START state
    if HMI.startPushed then {
        // (optional)
        // transition program: HMI.startPushed was true
        // when finished, go to START state
    } select START

    // next transition condition, with a transition failure program:
    if HMI.waiting then
      select WAIT else {
        // (optional)
        // transition failure program: HMI.startPushed was false

  handle {
     // only executed if no transition above could be made
     // if startPushed and waiting were false:
     // ... 

The transitions are checked in the same order as listed. A transition is allowed to select the current state, but the exit and entry functions will not be called in that case. Even more, a transition to the current state is always considered valid and this can not be overridden.

4.4.5. State Preconditions

Often it's useful to specify some preconditions that need to hold before entering a state. Orocos states explicitly allow for this. A state's preconditions will be checked before the state is entered.

Preconditions are specified as follows:

  state X {
    // make sure the robot is not moving axis 1 when entering this state
    // and a program is loaded.
    precondition  robot.movingAxis( 1 ) == false
    precondition  programLoaded == true
    // ...

They are checked in addition to transitions to that state and can make such a transition fail, hence block the transition, as if the transition condition in the first place did not succeed.

4.4.6. Event Transitions

An important property of state machines is that they can react to external (asynchronous) events. Since Orocos defined an Event framework in the CoreLib, this framework is used to react to events in this package.

Event transitions are specified as:

  state X {
    var int a, b
    var double d
    transition othertask.the_event(a, b, d) if (a+b & 10 && d >1.3) then {
       // transition succeeds, transition program:
       // ...
    } select ONE_STATE else {
       // transition fails, failure program:
       // ...
    } select OTHER_STATE

    // other events likewise...

Both the transition programs and the the select statements are optional, but at least a program or select statement must be given. In this example, othertask contains an event the_event. When the event the_event is emitted, our state machine reacts to it and the event arguments are stored in a, b and d. The if ... then statement may check these variables and any other state variables and methods to evaluate the transition. If it succeeds, an optional transition program may be given and a target state selected (ONE_STATE). if the transition fails, an optional failure program may be given and an optional select (OTHER_STATE) statement may be given. The number of arguments must match the number of arguments of the used event. The event is processed as an asynchronous callback, thus in the thread or task of the StateMachine's processor.

Event transitions are enabled after the entry program and before the exit program (also in automatic mode). All events are processed in a state until the first event that leads to a valid state transition. In the mean time, the run program or handle programs may continue, but will be interrupted if an event occurs. The event transition program and/or exit program may or must thus perform the necessary cleanup.

4.5. Instantiating Machines: SubMachines and RootMachines

As mentioned before: you can look at a SubMachine definition as the definition of a C++ class. It is merely the template for its instantiations, and you have to instantiate it to actually be able to do anything with it. There is also a mechanism for passing parameter values to the StateMachines on instantiation.

Note that you always need to write the instantiation after the definition of the StateMachine you're instantiating.

4.5.1. Root Machines

A Root Machine is a normal instantiation of a StateMachine, one that does not depend on a parent StateMachine ( see below ). They are defined as follows:

  StateMachine SomeStateMachine
      initial state initState
        // ...
      final state finalState
        // ...

  RootMachine SomeStateMachine someSMinstance 

This makes an instantiation of the StateMachine type SomeStateMachine by the name of 'someSMinstance', which can then be accessed from other scripts (by that name).

4.5.2. Parameters and public variables

StateMachine public variables

You can define variables at the StateMachine level. These variables are then accessible to the StateMachine methods (entry, handle, exit), the preconditions, the transitions and ( in the case of a SubMachine, see below ) the parent Machine.

You can define a StateMachine public variable as follows:

  StateMachine SomeStateMachine
    // a public constant
    const double pi = 3.1415926535897
    var int counter = 0

    initial state initState
            // change the value of counter...
            set counter = counter + 1
        // ...
    final state finalState
            do someTask.doSomethingWithThisCounter( counter )
        // ...

  Rootmachine SomeStateMachine mymachine 

This example creates some handy public variables in the StateMachine SomeStateMachine, and uses them throughout the state machine. They can also be read and modified from other tasks or programs :

  var int readcounter = 0
  set readcounter = taskname.states.mymachine.counter

  set taskname.states.mymachine.counter = taskname.states.mymachine.counter *  2
StateMachine parameters

A StateMachine can have parameters that need to be set on its instantiation. Here's an example:

  StateMachine AxisController
      // a parameter specifying which axis this Controller controls
      param int axisNumber
      initial state init
              var double power = someTask.getPowerForAxis( axisNumber )
  	    // do something with it...
  RootMachine AxisController axiscontroller1( axisNumber = 1 )
  RootMachine AxisController axiscontroller2( axisNumber = 2 )
  RootMachine AxisController axiscontroller3( axisNumber = 3 )
  RootMachine AxisController axiscontroller4( axisNumber = 4 )
  RootMachine AxisController axiscontroller5( axisNumber = 5 )
  RootMachine AxisController axiscontroller6( axisNumber = 6 )

This example creates an AxisController StateMachine with one integer parameter called axisNumber. When the StateMachine is instantiated, values for all of the parameters need to be given in the form "oneParamName= 'some value', anotherParamName = 0, yetAnotherParamName=some_other_expression + 5". Values need to be provided for all the parameters of the StateMachine. As you see, a StateMachine can of course be instantiated multiple times with different parameter values.

4.5.3. Building Hierarchies : SubMachines

A SubMachine is a StateMachine that is instantiated within another StateMachine ( which we'll call the parent StateMachine ). The parent StateMachine is owner of its child, and can decide when it needs to be started and stopped, by invoking the respective methods on its child.

Instantiating SubMachines

An instantiation of a SubMachine is written as follows:

  StateMachine ChildStateMachine
      initial state initState
          // ...
      final state finalState
          // ...
  StateMachine ParentStateMachine
      SubMachine ChildStateMachine child1
      SubMachine ChildStateMachine child2
      initial state initState
	      // enter initial state :
  	    do child1.activate()
  	    do child2.activate()
	      // enter final state :
              do child2.stop()
      final state finalState
	      // enter final state :
              do child1.stop()

Here you see a ParentStateMachine which has two ChildStateMachines. One of them is started in the initial state's entry method and stopped in its exit method. The other one is started in the initial state's entry method and stopped in the final state's entry method.

SubMachine manipulating

In addition to starting and stopping a SubMachine, a parent StateMachine can also inspect its public variables, change its parameters, and check what state it is in...

Inspecting StateMachine public variables is simply done using the syntax "someSubMachineInstName.someValue", just as you would do if someSubMachineInstName were an Orocos task. Like this, you can inspect all of a subcontext's public variables.

Setting a StateMachine parameter must be done at its instantiation. However, you can still change the values of the parameters afterwards. The syntax is: "set someSubMachine.someParam = someExpression". Here's an elaborate example:

  StateMachine ChildStateMachine
      param int someValue
      const double pi = 3.1415926535897
      initial state initState
          // ...
      final state finalState
          // ...

  StateMachine ParentStateMachine
      SubMachine ChildStateMachine child1( someValue = 0 )
      SubMachine ChildStateMachine child2( someValue = 0 )
      var int counter = 0
      initial state initState
  	      do child1.start()
  	      do child2.start()
              // set the subcontext's parameter
              set child1.someValue = 2
              set counter = counter + 1
              // set the subcontext's parameters
              set child2.someValue = counter
              // use the subcontext's public variables
              do someTask.doSomethingCool( child1.someValue )
              do child2.stop()
      final state finalState
              do child1.stop()

You can also query if a child State Machine is in a certain state. The syntax looks like:

someSubMachine.inState( "someStateName" )

4.6. Starting and Stopping StateMachines from scripts

Once a state machine is parsed and loaded into the State Machine Processor, it can be manipulated from another script. This can be done through the "states" subtask of the TaskContext in which the state machine was loaded. Assume that you loaded "machine" with subcontexts "axisx" and "axisy" in task "ATask", you can write

  do ATask.states.machine.activate()
  do ATask.states.machine.axisx.activate()
  // now in reactive mode...

  do ATask.states.machine.axisx.start()
  do ATask.states.machine.start()
  // now in automatic mode...

  do ATask.states.machine.stop()
  // again in reactive mode, in final state

  do ATask.states.machine.reset()
  do ATask.states.machine.deactivate()
  // deactivated.
  // etc. 

The first line activates a root StateMachine, thus it enters the initial state and is put in reactive mode , the next line actives its child, the next starts its child, then we start the parent, which bring both in automatic mode. Then the parent is stopped again, reset back to its initial state and finally deactivated.

Thus both RootMachines and SubMachines can be controlled. Some basic properties of the states can be inspected likewise :

  var bool res =  ATask.states.machine.isActive()      // Active ?
  set res = ATask.states.machine.axisy.isRunning()     // Running ?
  set res =  ATask.states.machine.isReactive()          // Waiting for requests or events? 
  var string current = ATask.states.machine.getState() // Get current state
  set res = ATask.states.machine.inState( current )    // inState ?

which makes it possible to monitor state machines from other scripts or an operator console.

4.6.1. On Reactive Mode Commands

Consider the following StateMachine :

  StateMachine X {
     // ...
     initial state y {
        entry {
	   // ...
        transitions {
	   // guard this transition.
           if checkSomeCondition() then
              select z
           if checkOtherCondition() then
              select exit
     state z {
       // ...
        transitions {
	   // always good to go to state :
	   select ok_1
     state ok_1 {
       // ...
     final state exit {
       // ...

  RootMachine X x

A program interacting with this StateMachine can look like this :

   program interact {
       // First activate x :
       do states.x.activate()  // activate and wait.

       // Request a state transition :
       try states.x.requestState("z") catch {
           // failed !

       // ok we are in "z" now, try to make a valid transition :
       do states.x.step()

       // enter pause mode :
       do states.x.pause()
       // Different ! Executes a single program statement :
       do states.x.step()

       // unpause, by re-entering reactive Mode :
       do states.x.reactive()

       // we are in ok_1 now, again waiting...
       do states.x.stop()      // go to the final state

       // we are in "exit" now
       do states.reset()

       // back in state "y", handle current state :
       do this.states.x.requestState( this.states.x.getState() )
       // etc.

The requestState command will fail if the transition is not possible ( for example, the state machine is not in state y, or checkSomeCondition() was not true ), otherwise, the state machine will make the transition and the command succeeds and completes when the z state is fully entered (it's init program completed).

The next command, step(), lets the state machine decide which state to enter, and since a transition to state "ok_1" is unconditionally, the "ok_1" state is entered. The stop() command brings the State Machine to the final state ("exit"), while the reset command sends it to the initial state ("y"). These transitions do not need to be specified explicitly, they are always available.

The last command, is a bit cumbersome request to execute the handle program of the current state.

At any time, the State Machine can be paused using pause(). The step() command changes to execute a single program statement or transition evaluation, instead of a full state transition.

All these methods can of course also be called from parent to child State Machine, or across tasks.

4.6.2. Automatic Mode Commands

Consider the following StateMachine, as in the previous section :

  StateMachine X {
     // ...
     initial state y {
        entry {
	   // ...
        transitions {
	   // guard this transition.
           if checkSomeCondition() then
              select z
           if checkOtherCondition() then
              select exit
     state z {
       // ...
        transitions {
	   // always good to go to state :
	   select ok_1
     state ok_1 {
       // ...
     final state exit {
       // ...

  RootMachine X x

A program interacting with this StateMachine can look like this :

   program interact {
       // First activate x :
       do states.x.activate()  // activate and wait.

       // Enter automatic mode :
       do states.x.start()

       // pause program execution :
       do states.x.pause()

       // execute a single statement :
       do states.x.step()

       // resume automatic mode again :
       do states.x.start()

       // stop, enter final state, in request mode again.
       do states.x.stop()

       // etc...

After the State Machine is activated, it is started, which lets the State Machine enter automatic mode. If checkSomeCondition() evaluates to true, the State Machine will make the transition to state "z" without user intervention, if checkOtherCondition() evaluates to true, the "exit" state will be entered.

When running, the State Machine can be paused at any time using pause(), and a single program statement ( a single line ) or single transition evaluation can be executed with calling step(). Automatic mode can be resumed by calling start() again.

To enter the reactive mode when the State Machine is in automatic mode, one can call the reactive() command, which will finish the program or transition the State Machine is making and will complete if the State Machine is ready for requests.

All these methods can of course also be called from parent to child State Machine, or across tasks.

5. Program and State Example

This sections shows the listings of an Orocos State Description and an Orocos Program Script. They are fictitious examples (but with valid syntax) which may differ from actual available tasks. The example tries to exploit most common functions.

Example 3.3. StateMachine Example (state.osd)

  StateMachine MachineMachine
      var bool error = false

       * This state is entered when the StateMachine is loaded.
       * The kernel is not running yet...
      initial state init_state {
  	transitions {
  	    select startup_state
       * Kernel is running, select the components.
      state startup_state {
  	entry {
  	    do Kernel.startComponent("HWSensor")
  	    do Kernel.startComponent("MoveToGenerator")
  	transitions {
  	    select stop_state
       * This state is only reached when the StateMachine
       * is stopped.
      final state fini_state {
  	entry {
  	    do Kernel.stopComponent("HWSensor")
  	    do Kernel.stopComponent("MoveToGenerator")
       * This state is the 'turn off' state of the
       * machine.
      state stop_state {
  	entry {
  	    // stop some components
  	    do Kernel.stopComponent("HWEffector")
  	    do Kernel.stopComponent("PIDController")
	    do PIDController.reset()
  	transitions {
  	    if HMI.start_pushed() && error == 0 then
  		 select run_state
       * This state puts the machine under 'control'
       * effectively accepting commands and driving
       * the machine.
      state run_state {
  	entry {
  	    // make sure we are not moving
  	    do MoveToGenerator.safeStop()
  	    // Select components controlling the machine
  	    do Kernel.startComponent("PIDController")
  	    do Kernel.startComponent("HWEffector")
  	transitions {
  	    if HMI.stop_pushed() then
  		 select stop_state
  	    if HMI.start_program() then
  		 select exec_state
       * This state starts a previously loaded
       * program.
      state exec_state {
  	entry {
  	    do programs.MyProgram.start()
  	exit {
	    set error = programs.MyPorgram.inError()
  	    do programs.MyProgram.stop()
  	transitions {
  	    if HMI.stop_program() then
  		 select run_state
	    // Detect Program Failure :
	    if programs.MyProgram.inError() then
	         select stop_state
  RootMachine MainMachine mainMachine

Example 3.4. Program example (program.ops)

   * This program is executed in the exec_state.
   * Request the HMI to load the user selected
   * trajectory into the kernel.
  export function HMILoadTrajectory() {
  	// request a 'push' of the next
  	// trajectory :
  	do HMI.requestTrajectory()
  	// when the HMI is done :
  	do Generator.loadTrajectory()
   * Do a Homing (reset) of the axes.
   * This could also be done using a Homing state,
   * without a program.
  export function ResetAxes() {
  	do Kernel.selectComponent("HomingGenerator")
  	do HomingGenerator.homeAll()
  export function ResetAxis(int nr) {
  	do Kernel.selectComponent("HomingGenerator")
  	do HomingGenerator.homeAxis( nr )
   * Request the Generator to use the current
   * trajectory.
  function runTrajectory() {
  	do Generator.startTrajectory()
  	// this function returns when the
  	// trajectory is done.
  program DemoRun {
  	do HMI.display("Program Started\n")
  	var int cycle = 0
  	// We actually wait here until a 
  	// Trajectory is present in the HMI.
  	do nothing until {
  	   if HMI.trajectoryPresent then continue
  	while HMI.cycle {
  	    do HMI.display("Cycle nr: %d.\n", cycle )
  	    do ResetAxes()
  	    do HMIRequestTrajectory()
  	    do runTrajectory()
  	    do Timer.sleep( 5.0 ) // wait 5s
  	do HMI.display("Program Ended\n")

Chapter 4. Distributing Orocos Components with CORBA


This document explains the principles of the Corba Library of Orocos, the Open RObot COntrol Software project. It enables transparant deployment of plain Orocos C++ components.

1. Overview

This package allows Orocos components to live in separate processes, distributed over an ethernet network and still communicate with each other. The underlying framework (middleware) is CORBA, but no CORBA knowledge is required to distribute Orocos components.

The Corba package provides:

  • Connection and Communication of Orocos components over a network

  • Clients (like visualisation) making a connection to any running Orocos component using the IDL interface.

  • Transparant use: existing Orocos applications only need to be recompiled.

1.1. Status

The Corba package is work in progress and aims to make the whole Orocos Component interface available over the network. Consult the Component Builder's Guide for an overview of a Component's interface.

These Component interfaces are currently available:

  • Properties/Attributes interface: fully

  • Command interface: fully

  • Method interface: fully

  • Scripting interface: fully

  • Data Flow interface: fully

These interfaces are work in progress and not yet available:

  • Event interface

1.2. Requirements and Setup

In order to distribute Orocos components over a network, your system must be setup correctly for using Corba.

The following must be done

  • Install the Ace and Tao libraries and header files on your system. Tao version 1.3 or 1.4.

  • Configure Orocos with Corba support. See the Getting Started Manual.

  • Load the 'Corba' package in your configuration tool, using make configure_packages. See the Getting Started Manual.

  • Start a Corba Naming Service once with multicasting on. Using the TAO Naming Service, this would be: Naming_Service -m 1 &

  • Compile your applications with the appropriate include and linker flags. See the Getting Started Manual.

1.3. Limitations

Orocos Corba components are work in progress. The following limitations apply:

  • Components can only communicate standard C++ types (double, int, string, etc.) and std::vector<double>. Adding user types is possible using the 'Toolkit Plugin' feature ( see also 'Orocos Type System' ).

  • Some Corba objects (for example 'commands') have a longer lifetime in memory than necessary. This does not cause harm in 'simple' setups, but is problematic when thousands of such objects are created.

2. Code Examples

This example assumes that you have taken a look at the 'Component Builder's Guide'. It creates a simple 'Hello World' component and makes it available to the network. Another program connects to that component and starts the component interface browser in order to control the 'Hello World' component. Both programs may be run on the same or on different computers, given that a network connection exists.

In order to setup your component to be available to other components transparantly, proceed as:

  // server.cpp
  #include <rtt/corba/ControlTaskServer.hpp>

  #include <rtt/PeriodicActivity.hpp>
  #include <rtt/TaskContext.hpp>
  #include <rtt/os/main.h>

  using namespace RTT;
  using namespace RTT::Corba;

  int ORO_main(int argc, char** argv)
     // Setup a component
     TaskContext mycomponent("HelloWorld");
     // Execute a component
     PeriodicActivity   myact(1, 0.01, mycomponent.engine() );

     // Setup Corba and Export:
     ControlTaskServer::InitOrb(argc, argv);
     ControlTaskServer::Create( &mycomponent );

     // Wait for requests:
     // Cleanup Corba:
     return 0;

Next, in order to connect to your component, you need to create a 'proxy' in another file:

  // client.cpp
  #include <rtt/corba/ControlTaskProxy.hpp>

  #include <rtt/TaskBrowser.hpp>
  #include <rtt/os/main.h>

  using namespace RTT::Corba;
  using namespace RTT;

  int ORO_main(int argc, char** argv)
     // Setup Corba:
     ControlTaskProxy::InitOrb(argc, argv);

     // Get a pointer to the component above
     TaskContext* component = ControlTaskProxy::Create( "HelloWorld" );

     // Interface it:
     TaskBrowser browse( component );

     // Cleanup Corba:
     return 0;

Both examples can be found in the corba-example package on You may use 'connectPeers' and the related methods to form component networks. Any Orocos component can be 'transformed' in this way.

3. Usage

When your Corba enabled component is running, the following usage rules should be known:

  • Components should not call remote components during real-time execution. However, real-time components may be called upon by any component, local or remote. A component may thus always receive a request from any component, but not every component may send a request to any component. If you violate this rule, it will not crash your program, but your execution timing will be worse.

  • If you call 'CORBA.shutdown()' upon a component, the whole CORBA part of that executable is shut down. It will cause the 'RunOrb()' function to return.

  • You need to export at least one component. If you try to access a peer component of that component over the network, this will be detected and the peer will be automatically exported as well. This means that if you visit each peer of a component, all these peer components will be known on the network.

4. Orocos Corba Interfaces

Orocos does not require IDL or CORBA knowledge of the user when two Orocos components communicate. However, if you want to access an Orocos component from a non-Orocos program (like a MSWindows GUI), you need to use the IDL files of Orocos.

The relevant files are:

  • ControlTask.idl: The main Component Interface file, providing CORBA access to a TaskContext.

  • Operations.idl: The interface of method and command objects.

  • OperationInterface.idl: The interface for accessing methods and commands.

  • ScriptingAccess.idl: The interface for loading and running scripts.

  • Attributes.idl: The interface for attributes and properties.

  • DataFlow.idl: The interface for communicating buffered or unbufferd data.

All data is communicated with CORBA::Any types. The way of using these interfaces is very similar to using Orocos in C++, but using CORBA syntax.

Chapter 5. Core Library Reference


This document explains the principles of the Core Library of Orocos, the Open RObot COntrol Software project. The CoreLib provides infrastructural support for the functional and application components of the Orocos framework.

1. Introduction

This Chapter describes the semantics of the services available in the Orocos Core Library.

The Core Library provides:

  • Thread-safe C++ implementations for periodic, non periodic and event driven activities

  • Synchronous/Asynchronous Events

  • Asynchronous Commands

  • Synchronous Methods

  • Properties and XML configuration

  • Time measurement

  • Application logging framework

  • Lock-free data exchange primitives such as fifo buffers or shared data.

and additionally provides interfaces which are common for all realtime services. The Core Library provides a hard realtime infrastructure:

The goal of the infrastructure is to keep applications deterministic, by avoiding the classical pitfalls of letting application programmers freely use threads and mutexes as bare tools. Practice has indeed showed that most programmers do not succeed in strictly decoupling the functional and algorithmic parts of their code from the OS-specific primitives used to execute them.

Of course, the realtime performance depends not only on the underlying operating system but also on the hardware. Hardware devices are abstracted in the Orocos Device Interface.

The following sections will first introduce the reader to creating Activities, which execute functions in a thread, in the system. Events allow callback functions to be executed when state changes occur. Commands are used to send instructions between threads. The following sections explain useful classes which are used throughout the framework such as the TimeService and Properties.

2. Periodic and non Periodic Activities


In older Orocos versions, 'Activities' were named 'Tasks'.

An Activity executes a function when a 'trigger' occurs. Although, ultimately, an activity is executed by a thread, it does not map one-to-one on a thread. A thread may execute ('serialise') multiple activities. This section gives an introduction to defining periodic activities, which are triggered periodically, non periodic activities, which are triggered by the user, and event driven activities, which are run when an Orocos event occurs.

2.1. Creating a Periodic Activity

If you want to execute functionality in one of the Orocos threads, you need to create a Activity of a certain type, depending on the thread type. The table below summarises which Activity type there is per thread.

Table 5.1. Thread and Activity summary

Thread (created by Orocos)Activity (created by User)

There are two ways to run a function in a periodic activity. By :

  • Implementing the RunnableInterface in another class ( functions initialize(), step() or loop()/breakLoop() and finalize() ). The RunnableInterface object (i.e. run_impl) can be assigned to a activity using
    	      &run_impl )

    or at construction time of an Activity :

     PeriodicActivity activity(priority,
    	      period, &run_impl );


      #include <rtt/RunnableInterface.hpp>
      #include <rtt/PeriodicActivity.hpp>
      class MyPeriodicActivity
    	: public RunnableInterface
        // ...
        bool initialize() {
           // your init stuff
           myperiod = this->getActivity()->getPeriod();
           isperiodic = this->getActivity()->isPeriodic();
           // ...
           return true; // if all went well
        // executed when isPeriodic() == true
        void step() {
           // periodic actions
        // executed when isPeriodic() == false
        void loop() {
           // 'blocking' version of step(). Implement also breakLoop()
        void finalize() {
           // cleanup
      // ...
      MyPeriodicActivity run_impl_1;
      MyPeriodicActivity run_impl_2;
      PeriodicActivity activity( 15, 0.01 ); // priority=15, period=100Hz &run_impl_1 );
      activity.start(); // calls 'step()'
      NonPeriodicActivity npactivity(12); // priority=12, no period. &run_impl_2);
      activity.start(); // calls 'loop()'
      // etc...  

  • Inheriting from an Activity class and overriding the initialize(), step() and finalize() methods.

      class MyOtherPeriodicActivity
          : public PeriodicActivity
      public :
          : PeriodicActivity( 15, 0.01 ) // priority=15, period=100Hz
        bool initialize() {
           // your init stuff
           double myperiod = this->getPeriod();
           // ...
           return true; // if all went well
        void step() {
           // periodic actions
        void finalize() {
           // cleanup
    	// ...
      // When started, will call your step
      MyOtherPeriodicActivity activity;

The Activity will detect if it must run an external RunnableInterface. If none was given, it will call its own virtual methods.

2.2. Periodic Activity Ordering

In case multiple activities are executed (serialised) in one thread, their execution must be ordered. The order of execution is determined by the order in which they are started. Stopping an activity removes it from the list.

Figure 5.1. Execution sequence diagram

Execution sequence diagram

A PeriodicActivity instance is only serialised with another instance if the priorities and periodicities match. Otherwise, a new thread is created.

2.3. Example Periodic Activity Creation

Example 5.1. Example Periodic Activity Creation

This example shows how all kinds of activities can be created. When a activity is started it will add itself to the correct thread.

#include "rtt/PeriodicActivity.hpp"

using namespace RTT;

ORO_main( int argc, char** argv)
  // Define your tasks.

  // ...

  // The threads are created by Orocos.
  // Both activities run in the same thread:
  PeriodicActivity fast_activity1(0, 0.001, &vel_loop);
  PeriodicActivity fast_activity2(0, 0.001, &vel_loop2);

  // This activity is run in its own thread.
  PeriodicActivity own_activity( 9, 0.05, &kine_loop );

  // This activity is run in its own thread as well.
  PeriodicActivity own_activity2( 9, 0.5, &kine_loop2 );

  // All is transparant from here on.
  fast_activity2->start(); // is always run directly after fast_activity1 !

  // ...


  return 0;

2.4. Non Periodic Activities

Non periodic activities are run in non periodic threads, or possibly after all periodic activities of a certain periodic thread. The latter to avoid excessive jitter in periodic activity execution.

If you want to create an activity which reads file-IO, or displays information or does any other possibly blocking operation, the NonPeriodicActivity implementation can be used. When it is start()'ed, its loop() method will be called exactly once and then it will wait, after which it can be start()'ed again. Analogous to periodic activities, the user can implement initialize(), loop() and finalize() functions in a RunnableInterface which will be used by the activity for executing the user's functions. Alternatively, you can reimplement said functions in a derived class of NonPeriodicActivity. The activity's loop() will be executed in its own thread, thus creating a NonPeriodicActivity means creating a new thread :

  int priority = 5;
  RunnableInterface* blocking_activity = ...
  NonPeriodicActivity activity( priority, blocking_activity );
  activity.start(); // calls blocking_activity->initialize()

  // now blocking_activity->loop() is called in a thread with priority 5.  
  // assume loop() finished...

  activity.start();  // executes again blocking_activity->loop()

  // calls blocking_activity->breakLoop() if loop() is still executing,
  // when loop() returned, calls blocking_activity->finalize() :

The NonPeriodicActivity differs from the PeriodicActivity in the way start() and stop() work. Only the first invocation of start() will invoke initialize(). Then loop() is executed once. Since the activity may be blocked in the user's loop() function, the user must reimplement the RunnableInterface::breakLoop() function. This funcion must do whatever necessary to let the user's loop() function return (mostly set a flag). It must return true on success, false if it was unable to let the loop() function return (the latter is the default implementation's return value). stop() then waits until loop() returns or aborts if breakLoop() returns false. When successful, stop() executes the finalize() function.

2.5. Custom or Slave Activities

If non of the above activity schemes fit you, you can always fall back on the SlaveActivity, which lets the user control when the activity is executed. A special function bool trigger() is implemented which will execute RunnableInterface::step() or RunnableInterface::loop() when called by the user. Three versions of the SlaveActivity can be constructed:

  #include <rtt/SlaveActivity.hpp>

  // With master
  // a 'master', any ActivityInterface (even SlaveActivity):
  PeriodicActivity master_one(9, 0.001 );
  // a 'slave', takes over properties (period,...) of 'master_one':
  SlaveActivity slave_one( &master_one );

  slave_one.start();   // fail: master not running.
  slave_one.trigger(); // fail: slave not running.

  master_one.start();  // start the master.
  slave_one.start();   // ok: master is running.
  slave_one.trigger(); // ok: calls step(), repeat...
  // Without master
  // a 'slave' without explicit master, with period of 1KHz.
  SlaveActivity slave_two( 0.001 );
  // a 'slave' without explicit master, not periodic.
  SlaveActivity slave_three();

  slave_two.start();   // ok: start periodic without master
  slave_two.trigger(); // ok, calls 'step()', repeat...

  slave_three.start();   // start not periodic.
  slave_three.trigger(); // ok, calls 'loop()', may block !
  // if loop() blocks, trigger() blocks as well.

Note that although there may be a master, it is still the user's responsibility to call trigger().

2.6. Accessing the Threads from Activities

Each Orocos Activity (periodic, non periodic and event driven) type has a thread() method in its interface which gives a non-zero pointer to a ThreadInterface object which provides general thread information such as the priority and periodicity and allows to control the realtimeness of the thread which runs this activity. A non periodic activity's thread will return a period of zero.

A RunnableInterface can get the same information through the this->getActivity()->thread() method calls.

Example 5.2. Example Periodic Thread Interaction

This example shows how to manipulate a thread.

#include "rtt/ActivityInterface.hpp"

using namespace RTT;

ORO_main( int argc, char** argv)
  // ... create any kind of Activity like above.

  ActivityInterface* act = ...

  // stop the thread and all its activities:
  // change the period:
  act->thread()->setPeriod( 0.01 );
  // Optional :

  // Now the activity can be started as well:

  // act is running...

  return 0;

2.7. Simulation

The SimulationThread is available to do as fast as possible execution of SimulationActivity objects. Its priority and simulated periodicity can be changed with the configuration tool, or before its started.

#include "rtt/SimulationActivity.hpp"

using namespace RTT;

ORO_main( int argc, char** argv)
  // Define your activities

  // ...

  // Manually start the simulation thread
  // 0.001 : The (virtual) period :  no activity can run 'faster' than this.
  SimulationThread::Instance()->setPeriod( 0.001 );

  // Optional, might hang your program :

  // fast_sim_activity will measure 0.001s elapses between each step(),
  // slow_sim_activity will measure 0.01s elapses in time between each step()
  SimulationActivity fast_sim_activity(0.001, &vel_loop);
  SimulationActivity slow_sim_activity(0.01, &pos_loop);

  // All is transparant from here on.

  // ...


  return 0;

If other threads are running in the same program executable, they will also 'notice' the fast system time changes if the SimulationThread is started. It is thus advisable not to mix SimulationThreads with other threads. Also, any thread with lower priority than the SimulationThread will never run.

3. Commands

Commands offer a thread-safe realtime means of message passing between threads.

3.1. The Command Processor

The CommandProcessor is responsible for accepting command requests from other (realtime) tasks. It uses a non-blocking queue to store incoming requests and fetch-and-execute them in its periodic step.

Figure 5.2. Tasks Sending Commands

Tasks Sending Commands

Tasks of different threads communicate by sending commands to each other's Command Processors. When Task T1, running in Thread (a), requests that T2, running in Thread (b) processes a command, the command is stored in a command queue of that task's Command Processor. When T2 runs its Command Processor, the queue is checked and the command is executed. T1 can optionally check if the command was accepted and executed, using a Completion Condition ( see TaskContext and Program Parser manuals. )

4. Events

An Event is an object to which one can connect callback functions. When the Event is raised, the connected functions are called one after the other. An Event can carry data and deliver it to the function's arguments. Orocos allows two possibilities of calling the function : synchronous and asynchronous. The former means that when the event is called, all synchronous handlers are called in the same thread. The latter means that the data is stored and the callback function is called in another thread. The thread which will execute the deferred callback is chosen at connection or setup time.

Figure 5.3. Event Handling

Event Handling

Activity A1 runs in PeriodicThread (a) while Activity A2 runs in PeriodicThread (b). At some time, A1 registers a synchonous and asynchronous callback function ( reaction ) with activity A2's Event. When A2 emits the Event, the synchronous Event callback is executed first ( within Thread (b) ), while the asynchronous ( deferred ) callback is queued and executed after A1 has run, in Thread (a).

The Orocos Event extends the signal semantics with asynchronous event handling. Any kind of function can be connected to the event as long as it has the same signature as the Event. 'Raising', 'fireing' or 'emiting' an Orocos Event is done by using the () operator.

4.1. Event Basics

Example 5.3. Using Events

An Event must always be given a name upon construction. Providing it a name tells Orocos that it should be initialised as a full functioning object. This example shows how a synchronous and asynchronous handler are connected to an Event.

#include <rtt/Event.hpp>

using boost::bind;

class SafetyStopRobot
    void handle_now() {
        // Synchronous Handler code
    std::cout << " Putting the robot in a safe state fast !" << std::endl;

Class NotifyUser
    void handle_later() {
	    //Asynchronous Completer code
	    std::cout << "The program stopped the robot !"<<std::endl;

SafetyStopRobot safety;
NotifyUser      notify;

// The <..> means the callback functions must be of type "void foo(void)"
Event<void(void)> emergencyStop("EmergencyStop");
// Use ready() to see if the event is initialised.
assert( emergencyStop.ready() );
Handle emergencyHandle;
Handle notifyHandle;

// boost::bind is a way to connect the method of an object instance to
// an event.
std::cout << "Register apropriate handlers to the Emergency Stop Event\n";
emergencyHandle = 
   emergencyStop.connect( bind( &SafetyStopRobot::handle_now, &safety));
assert( emergencyHandle.connected() );

notifyHandle = 
   emergencyStop.connect( bind( &NotifyUser::handle_later, &notify),
                          CompletionProcessor::Instance() );
assert( notifyHandle.connected() );

std::cout << "Emit/Call the event\n";

// Disconnecting the notify callback...

// Only synchronous callback :
std::cout << "Doing a quiet safety stop..."<<std::endl;
emergencyStop(); // User not notified
	  Register apropriate handlers to the Emergency Stop Event
	  Emit the event
	   Putting the robot in a safe state fast !
	  The program stopped the robot !
	  Doing a quiet safety stop...
	   Putting the robot in a safe state fast !

If you want to find out how boost::bind works, see the Boost bind manual. You must use bind if you want to call C++ class member functions to 'bind' the member function to an object :

  ClassName object;
  boost::bind( &ClassName::FunctionName, &object)	

Where ClassName::FunctionName must have the same signature as the Event. When the Event is called,

  object->FunctionName( args )

is executed by the Event.

When you want to call free ( C ) functions, you do not need bind :

  Event<void(void)> event;
  void foo() { ... }
  event.connect( &foo );

Whether your handle() and complete() methods contain deterministic code or not is up to you. It depends on the choice of the Event type and in which thread it is executed. A good rule of thumb is to make all Synchronous handling/completing deterministic time and do all the rest in the Asynchronous part, which will be executed by the another thread.

You must choose the type of Event upon construction. This can no longer be changed once the Event is created. The type is the same for the synchronous and asynchronous methods. If the type changes, the event() method must given other arguments. For example :

Example 5.4. Event Types

  Event<void(void)> e_1("e_1");

  Event<void(int)>  e_2("e_2");
  e_2( 3 );

  Event<void(double,double,double)>  positionEvent("p");
  positionEvent( x, y, z);

Furthermore, you need to setup the connect call differently if the Event carries one or more arguments :

  SomeClass someclass;

  Event<void(int, float)> event("event");

  // notice that for each Event argument, you need to supply _1, _2, _3, etc...
  event.connect( boost::bind( &SomeClass::foo, someclass, _1, _2 ) );

  event( 1, 2.0 );


The return type for synchronous and asynchronous callbacks is ignored and can not be recovered.

4.2. setup() and the Handle object

Event connections can be managed by using a Handle which both connect() and setup() return :

  Event<void(int, float)> event("event");
  Handle eh;

  // store the connection in 'eh'
  eh = event.connect( ... );
  assert( eh.connected() );

  // disconnect the function(s) :
  assert( !eh.connected() );

  // reconnect the function(s) :
  // connected again !

Handle objects can be copied and will all show the same status. To have a connection setup, but not connected, one can write :

  Event<void(int, float)> event)("event");
  Handle eh;

  // setup : store the connection in 'eh'
  eh = event.setup( ... );
  assert( !eh.connected() );

  // now connect the function(s) :
  assert( eh.connected() );  // connected !

If you do not store the connection of setup(), the connection will never be established and no memory is leaked. If you do not use 'eh' to connect and destroy this object, the connection is also cleaned up. If you use 'eh' to connect and then destroy 'eh', you can never terminate the connection, except by destroying the Event itself.

4.3. Choosing the Asynchronous Thread

As mentioned before, the asynchronous callback is executed in another thread than the event caller. The Event implementation provides one thread for asynchronous execution, the CompletionProcessor. You can intercept asynchronous events in your thread using the EventProcessor class.


For brevity, we will not use boost::bind in the following examples and only use 'free' ( C ) functions as callbacks. Asynchronous callbacks are bound in the same way as synchronous callbacks ( Example 5.3, “Using Events” ) :

  void syn_func( int, double ) { /* .. */ }
  void asyn_func( int, double )  { /* .. */ }

The default thread which executes asynchronous callbacks is called the CompletionProcessor. This is a non realtime thread, which means that the reaction time is not bounded. If you want to execute the callback in another thread, an additional argument can be given in the connect or setup method :

  EventProcessor eproc;
  PeriodicActivity my_act(1, 0.01, &eproc );

  event.connect( &asyn_func, &eproc );

The above lists how the an EventProcessor will execute the asyn_func if event is emited. The EventProcessor is not a thread itself, but an object which can be executed by an activity. If you want to both process events and insert application code in the same activity object, you'll need to call the EventProcessor's initialize(), step() and finalize() functions manually. See the RunnableInterface documentation.


Event handlers can have no more than 4 arguments in the current implementation, but more can be added upon request. Since a struct or class can be used as arguments, the need is fairly low though.

4.4. Event Overrun Policy

An Event can only be emited by one thread at the same time. The synchronous handlers will always be executed as much times as the event is emited. This is not the case for asynchronous handlers. If an Event is emited multiple times before the completion thread executes, the asynchronous handler will be called only once in the completion thread's execution step.

The question that rises is with which arguments this handler is called. The user can choose between the first (default) and the last. The first is choosen as default because this causes the least overhead in execution time. To choose which policy is used, an optional parameter can be given during connect :

  event.connect( &asyn_func, eproc, Event::OnlyLast );
  event.connect( &asyn_func, eproc, Event::OnlyFirst ); // default
  event.connect( &asyn_func, eproc ); // same as previous line

4.5. The Completion Processor

The CompletionProcessor is an optional lowest priority, not realtime thread in the Orocos framework. It is only created if the user did not specify a thread in which to process events.

Its purpose is to execute asynchronous event callbacks that have to be `completed' when no other work has to be done. The only constraint it imposes is that all functions it executes must require finite time to complete (it cannot detect timeouts). You can get its thread pointer like this :

 #include <rtt/CompletionProcessor.hpp>

  ActivityInterface* cp = CompletionProcessor::Instance()

The CompletionProcessor is a NonPeriodicActivity, thus not consuming time resources when no Events need to be processed. If you need a hard realtime CompletionProcessor, use a default NonPeriodicActivity ( see Section 2.4, “Non Periodic Activities” ), call its makeHardRealTime() method and add an EventProcessor object in run().

If you want to process Events in your own RunnableInterface implementation, you need to manually call the step() method of the EventProcessor :

  // in your implementation :
  void loop() {
     while ( ... ) {
        // < do non periodic stuff >
        // process any pending Events :
  // ...  

5. Time Measurement and Conversion

5.1. The TimeService

The TimeService is implemented using the Singleton design pattern. You can query it for the current (virtual) time in clock ticks or in seconds. The idea here is that it is responsible for synchronising with other (distributed) cores, for doing, for example compliant motion with two robots. This functionality is not yet implemented though.

When the SimulationThread is used and started, it will change the TimeService's clock with each period ( to simulate time progress). Also other threads (!) In the system will notice this change, but time is guaranteed to increase monotonously.

5.2. Usage Example

Also take a look at the interface documentation.

  #include <rtt/TimeService.hpp>
  #include <rtt/Time.hpp>

  TimeService::ticks timestamp = TimeService::Instance()->getTicks();

  Seconds elapsed = TimeService::Instance()->secondsSince( timestamp );	

6. Attributes

Attributes are class members which contain a (constant) value. Orocos can manipulate a classes attribute when it is wrapped in an Attribute class. This storage allows it to be read by the scripting engine, to be displayed on screen or manipulated over a network connection.

The advantages of this class come clear when building Orocos Components, since it allows a component to export internal data.

Example 5.5. Creating attributes

  // an attribute, respresening a double of value 1.0:
  Attribute<double> myAttr(1.0);
  myAttr.set( 10.9 );
  double a = myAttr.get(); 

  // read-only attribute:
  Constant<double> pi(3.14);
  double p = pi.get();

7. Properties

Properties are more powerful than attributes (above) since they can be stored to an XML format, be hierarchically structured and allow complex configuration.

7.1. Introduction

Orocos provides configuration by properties through the Property class. They are used to store primitive data (float, strings,...) in a hierachies (using PropertyBag). A Property can be changed by the user and has immediate effect on the behaviour of the program. Changing parameters of an algorithm is a good example where properties can be used. Each parameter has a value, a name and a description. The user can ask any PropertyBag for its contents and change the values as they see fit. Java for example presents a Property API. The Doxygen Property API should provide enough information for succesfully using them in your Software Component.


Reading and writing a properties value can be done in realtime. Every other transaction, like marshalling (writing to disk), demarshalling (reading from disk) or building the property is not a realtime operation.

Example 5.6. Using properties

  // a property, respresening a double of value 1.0:

  Property<double> myProp("Parameter A","A demo parameter", 1.0); // not realtime !
  myProp = 10.9; // realtime
  double a = myProp.get(); // realtime  

Properties are mainly used for two purposes. First, they allow an external entity to browse their contents, as they can form hierarchies using PropertyBags. Second, they can be written to screen, disk, or any kind of stream and their contents can be restored lateron, for example after a system restart. The next sections give a short introduction to these two usages.

7.2. Grouping Properties in a PropertyBag

First of all, a PropertyBag is not the owner of the properties it owns, it merely keeps track of them, it defines a logical group of properties belonging together. Thus when you delete a bag, the properties in it are not deleted, when you clone() a bag, the properties are not cloned themselves. PropertyBag is thus a container of pointers to Property objects.

If you want to duplicate the contents of a PropertyBag or perform recursive operations on a bag, you can use the helper functions we created and which are defined in PropertyBag.hpp (see Doxygen documentation). These operations are however, most likely not realtime.


When you want to put a PropertyBag into another PropertyBag, you need to make a Property<PropertyBag> and insert that property into the first bag.

Use add to add Properties to a bag and getProperty<T> to mirror a Property<T>. Mirroring allows you to change and read a property which is stored in a PropertyBag: the property object's value acts like the original. The name and description are not mirrored, only copied upon initialisation:

  PropertyBag bag;
  Property<double> w("Weight", "in kilograms", 70.5 );
  Property<int> pc("PostalCode", "", 3462 );

  struct BirthDate {
     BirthDate(int d, month m, int y) : day(d), month(m), year(y) {}
     int day;
     enum { jan, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec} month;
     int year;

  Property<BirthDate> bd("BirthDate", " in 'BirthDate' format", BirthDate(1, apr, 1977));

  bag.add( &w );
  bag.add( &pc );
  bag.add( &bd );

  // setup mirrors:	
  Property<double> weight = bag.getProperty<double>("Weight");
  assert( weight.ready() );

  // values are mirrored:
  assert( weight.get() == w.get() );
  weight.set( 90.3 );
  assert( weight.get() == w.get() );

  Property<BirthDate> bd_bis;
  assert( ! bd_bis.ready() );
  bd_bis = bag.getProperty<BirthDate>("BirthDate");
  assert( bd_bis.ready() );

  // descriptions and names are not mirrored:
  assert( bd_bis.getName() == bd.getName() );
  assert( bd_bis.getName() != bd.getName() );

7.3. Marshalling and Demarshalling Properties (Serialization)

Marshalling is converting a property C++ object to a format suitable for transportation or storage, like XML. Demarshalling reconstructs the property again from the stored format. In Orocos, the Marshaller interface defines how properties can be marshalled. The available marshallers (property to file) in Orocos are the TinyMarshaller, XMLMarshaller, XMLRPCMarshaller, INIMarshaller and the RTT::CPFMarshaller (only if Xerces is available).

The inverse operation (file to property) is currently supported by two demarshallers: TinyDemarshaller and the RTT::CPFDemarshaller (only if Xerces is available). They implement the Demarshaller interface.

The (de-)marshallers know how to convert native C++ types, but if you want to store your own classes in a Property ( like BirthDate in the example above ), the class must be added to the Orocos type system.

8. The NameServer

8.1. Introduction

A useful element in the Orocos framework is what we call the strong typed nameserver. It is a (string based) nameserver which stores name, object pairs of only one type of object in the local program. Off course, polymorphism allows us to collect many derivative types into one nameserver. A nameserver allows late configuration of objects. All possible used objects are created first and stored in the nameserver. Depending of the run-time users choice (from a text file, console input,...), another object is retrieved from the nameserver and used in the program.

8.2. Using the NameServer

The local object server is called NameServer. The most common usage syntax is given below.


The most common use of nameserving is keeping track of pointers to objects. A NameServer almost always takes pointers to an object as arguments and returns a pointer when the object is looked up again.

  // A NameServer collecting pointers to ClassA objects
  NameServer< ClassA* > nameserver;
  ClassA my_a;
  nameserver.registerObject( &my_a, "ATeam" );
  // ...
  ClassA* an_a = nameserver.getObject( "ATeam" );
  if (an_a != 0 )
      cout << "ATeam was successfully stored and retrieved !" >> endl;     

A typical use of nameserving is that the nameserver is nested inside the class it is nameserving itself. For convenience, the constructor of that class is then extended to take a string as argument to indicate the (optional) desired name of the object. Imagine that the above ClassA had such a nested nameserver, in that case, it would be used as follows :

  ClassA my_a( "The ATeam" ); // give name in constructor
  // ...
  // notice the scope ClassA:: the nameserver is nested in :
  ClassA* an_a = ClassA::nameserver.getObject( "The ATeam" );
  if (an_a != 0 )
    cout << "The ATeam was successfully stored and retrieved !" >> endl;     

The above technique is used in many classes inside Orocos. Events, Devices, Control Kernels and Components, ... anything you wish to configure at runtime can be nameserved.

9. Buffers and DataObjects

Orocos provides some basic inter-thread buffering mechanisms in the rtt/buffers package.

The difference between Buffers and DataObjects is that DataObjects always contain a single value, while buffers may be empty, full or contain a number of values. Thus a DataObject always returns the last value written (and a write always succeeds), while a buffer may implement a FIFO queue to store all written values (and thus can get full).

Figure 5.4. DataObjects versus Buffers

DataObjects versus Buffers

DataObjects are most suitable for single writer, many readers, and always return the last written value. Buffers have a fixed queue length and are used for processing all produced data by any number of producers and consumers.

9.1. Buffers

The BufferInterface<T> provides the interface for Orocos buffers. Currently the BufferLockFree<T> is a typed buffer of type T and works as a FIFO queue for storing elements of type T. It is lock-free, non blocking and read and writes happen in bounded time. It is not subject to priority inversions.

Example 5.7. Accessing a Buffer

  #include <rtt/BufferLockFree.hpp>

  // A Buffer may also contain a class, instead of the simple
  // double in this example
  // A buffer with size 10:
  BufferLockFree<double> my_Buf( 10 ); 
  if ( my_Buf.Push( 3.14 ) ) {
     // ok. not full.
  double  contents; 
  if ( my_Buf.Pop( contents ) ) {
     // ok. not empty.
     // contents == 3.14

Both Push() and Pop() return a boolean to indicate failure or success.

9.2. DataObjects

The data inside the DataObjects can be any valid C++ type, so mostly people use classes or structs, because these carry more semantics than just (vectors of) doubles. The default constructor of the data is called when the DataObject is constructed. Here is an example of creating and using a DataObject :

Example 5.8. Accessing a DataObject

  #include <rtt/DataObjectInterfaces.hpp>

  // A DataObject may also contain a class, instead of the simple
  // double in this example
  DataObjectLockFree<double> my_Do("MyData"); 
  my_Do.Set( 3.14 ); 
  double  contents; 
  my_Do.Get( contents );   // contents == 3.14
  contents  = my_Do.Get(); // equivalent  

The virtual DataObjectInterface interface provides the Get() and Set() methods that each DataObject must have. Semantically, Set() and Get() copy all contents of the DataObject.

10. Logging

Orocos applications can have pretty complex startup and initialisation code. A logging framework, using Logger helps to track what your program is doing.


Logging can only be done in the non-realtime parts of your application, thus not in the Realtime Periodic Activities !

There are currently 8 loglevels :

Table 5.2. Logger Log Levels

-1naCompletely disable logging
0Logger::NeverNever log anything (to console)
1Logger::FatalOnly log Fatal errors. System will abort immediately.
2Logger::CriticalOnly log Critical or worse errors. System may abort shortly after.
3Logger::ErrorOnly log Errors or worse errors. System will come to a safe stop.
4Logger::Warning[Default] Only log Warnings or worse errors. System will try to resume anyway.
5Logger::InfoOnly log Info or worse errors. Informative messages.
6Logger::DebugOnly log Debug or worse errors. Debug messages.
7Logger::RealTimeLog also messages from possibly Real-Time contexts. Needs to be confirmed by a function call to Logger::allowRealTime().

You can change the amount of log info printed on your console by setting the environment variable ORO_LOGLEVEL to one of the above numbers :

  export ORO_LOGLEVEL=5

The default is level 4, thus only warnings and errors are printed.

The minimum log level for the orocos.log file is Logger::Info. It will get more verbose if you increase ORO_LOGLEVEL, but will not go below Info. This file is always created if the logging infrastructure is used. You can inspect this file if you want to know the most useful information of what is happening inside Orocos.

If you want to disable logging completely, use

export ORO_LOGLEVEL=-1

before you start your program.

For using the Logger class in your own application, consult the API documentation.

Example 5.9. Using the Logger class

  #include <rtt/Logger.hpp>

  Logger::In in("MyModule");
  log( Error ) << "An error Occured : " << 333 << "." << endlog();
  log( Debug ) << debugstring << data << endlog();
  log() << " more debug info." << data << endlog();
  log() << "A warning." << endlog( Warning );

As you can see, the Logger can be used like the standard C++ input streams. You may change the Log message's level using the LogLevel enums in front (using log() ) or at the end (using endlog()) of the log message. When no log level is specified, the previously set level is used. The above message could result in :

  0.123 [ ERROR  ][MyModule] An error Occured : 333
  0.124 [ Debug  ][MyModule] <contents of debugstring and data >
  0.125 [ Debug  ][MyModule]  more debug info. <>
  0.125 [ WARNING][MyModule] A warning.

Chapter 6. OS Abstraction Reference


This document gives a short overview of the philosophy and available classes for Operating System ( threads, mutexes, etc ) interaction within Orocos

1. Introduction

1.1. Realtime OS Abstraction

The OS package makes an abstraction of the operating system on which it runs. It provides C++ interfaces to only the minimal set of operating system primitives that it needs: mutexes, semaphores and threads. This is in accordance with the general developers requirements of the project: a minimalistic approach is much easier to scale, to maintain, and to port. The abstraction also allows Orocos users to build their software on all supported systems with only a recompilation step. The OS Abstraction layer is not directly being used by the application writer. Basic OS primitives are leading programmers to often to pitfalls which can be avoided using well known solutions. These solutions are implemented in the CoreLib classes and allow the programmer to think in a more natural way about the problem.

The abstractions cause (almost) no execution overhead, because the wrappers can be called inline. See the OROBLD_OS_AGNOSTIC option in the configuration tool to control inlining.

2. The Operating System Interface

2.1. Basics

Keeping the Orocos core portable requires an extra abstraction of some operating system (OS) functionalities. For example, a thread can be created, started, paused, scheduled, etc., but each OS uses other function calls to do this. Orocos prefers C++ interfaces, which led to the ThreadInterface which allows control and provides information about a thread in Orocos.

Three thread classes are available in Orocos: PeriodicThread houses a periodic thread and SingleThread is a non periodic thread which executes the functionality once each time it is started. The MainThread is a special case as only one such object exists and represents the thread that executes the main() function.

This drawing situates the Operating System abstraction with respect to device driver interfacing (DI) and the rest of Orocos

Figure 6.1. OS Interface overview

OS Interface overview

3. OS Package Structure

The OS package has a common directory for all common interfaces and configuration options. This directory is OS independent but may contain assembler instructions ( such as Compare And Swap ) for specific processor architectures. However, if Orocos grows to support many different architectures, an arch directory will most likely be introduced to sort files for specific architectures. Next to the common directory is a <target> directory which contains the abstraction implementations for a specific OS. Multiple OS abstractions may be available, but only one can be configured and compiled in one configuration.

3.1. The RTAI/LXRT OS target

RTAI/LXRT is an environment that allows user programs to run with realtime determinism next to the normal programs. The advantage is that the realtime application can use normal system libraries for its functioning, like showing a graphical user interface.

An introduction to RTAI/LXRT can be found in the Porting to LXRT HOWTO, which is a must-read if you don't know what LXRT is.

The common rule when using LXRT is that any userspace (GNU/Linux) library can be used and any header included as long as their non-realtime functions are not called from within a hard realtime thread. Specifically, this means that all the RTAI (and Orocos) OS functions, but not the native Linux ones, may be called from within a hard realtime thread. Fortunately these system calls can be done from a not hard realtime thread within the same program.

3.2. Porting Orocos to other Architectures / OS'es

The OS package is the only part of Orocos that needs to be ported to other Operating Sytems or processor architectures in case the target supports Standard C++. The os/common directory contains code common to all OS'es and the architecture dependent headers (for example atomic counters and compare-and-swap ). The latter must be extended to support other processor architectures. Also, when a processor architecture is added, it must be made available in the os.cdl configuration file, allowing the user to change the target processor.

In order to start your port, look at the fosi_interface.h and fosi_internal_interface.h files in the os/common package. These two files list the C function signatures of all to be ported functions in order to support a new OS. The main categories are: time reading, mutexes, semaphores and threads. The easiest way to port Orocos to another operating sytem, is to copy the gnulinux package into a new target and start modifying the functions to match those in your OS. This package is recommended because it uses the standard Unix/Posix functions.

3.3. OS Header Files

The following table gives a short overview of the available headers in the OS package.

Table 6.1. Header Files

LibraryWhich file to includeRemarks
OS functionalityrtt/os/fosi.hInclude this file if you want to make system calls to the underlying operating system ( LXRT, GNU/Linux ) .
OS Abstraction classes Mutex.hpp, MutexLock.hpp, Semaphore.hpp, PeriodicThread.hpp, SingleThread.hpp, main.h The available C++ OS primitives. main.h is required to be included in your ORO_main() program file.

4. Using Threads and Realtime Execution of Your Program

4.1. Writing the Program main()

All tasks in the realtime system have to be performed by some thread. The OS abstraction expects an int ORO_main(int argc, char** argv) function (which the user has written) and will call that after all system initialisation has been done. Inside ORO_main() the user may expect that the system is properly set up and can be used. The resulting orocos-rtt library will contain the real main() function which will call the ORO_main() function.


Do not forget to include <rtt/os/main.h> in the main program file, or the linker will not find the ORO_main function.


Using global objects ( or static class members ) which use the OS functions before ORO_main() is entered (because they are constructed before main() ), can come into conflict with an uninitialised system. It is therefor advised not to use static global objects which use the OS primitives. Events in the CoreLib are an example of objects which should not be constructed as global static. You can use dynamically created (i.e. created with new ) global events instead.

4.2. The Orocos Thread System

4.2.1. Periodic Threads

An Orocos thread, which must execute a task periodically, is defined by the PeriodicThread. The most common operations are start(), stop() and setting the periodicity. What is executed is defined in an user object which implements the RunnableInterface. It contains three methods : initialize(), step() and finalize(). You can inherit from this interface to implement your own functionality. In initialize(), you put the code that has to be executed once when the component is start()'ed. In step(), you put the instructions that must be executed periodically. In finalize(), you put the instructions that must be executed right after the last step() when the component is stop()'ed.

However, you are encouraged NOT to use the OS classes! The CoreLib uses these classes as a basis to provide a more fundamental activity-based (as opposite to thread based) execution mechanism which will insert your periodic activities in a periodic thread.

Common uses of periodic threads are :

  • Running periodic control tasks.

  • Fetching periodic progress reports.

  • Running the corelib periodic tasks.

4.2.2. Non Periodic Threads

For non-periodic threads, which block or do lenghty calculations, the SingleThread class can be used. The rtt/activities package uses the SingleThread for the NonPeriodicActivity. Porting applications to Orocos might benifit this class in a first adaptation step. It has a start() method, which will invoke one single call to the user's loop() function ( in contrast to step() above). It can be re-started each time the loop() function returns. The initialise() functions is called when the SingleThread is started the first time. When stopped, the finalise() function is called after loop() returns.

The user himself is responsible for providing a mechanism to return from the loop() function. The SingleThread expects this mechanism to be implemented in the RunnableInterface::breakLoop() function, which must return true if the loop() function could be signaled to return. SingleThread will call breakLoop() in its stop() method if loop() is still being executed and, if succesful, will wait until loop() returns. The SingleThread::isRunning() function can be used to check if loop() is being executed or not.


The NonPeriodicActivity in CoreLib provides a better integrated implementation for SingleThread and should be favourably used.

Common uses of non periodic threads are :

  • Listening for data on a network socket.

  • Reading a file or files from harddisk.

  • Waiting for user input.

  • Execute a lengthy calculation.

  • React to asynchronous events.

The user of this class must be aware that he must provide himself the locking primitives (like RTT::OS::Mutex) to provide thread safety.

4.2.3. Setting the Scheduler and Priorities.

The Orocos thread priorities are set during thread construction time and can be changed later on with setPriority. Priorities are integer numbers which are passed directly to the underlying OS. One can use priorities portably by using the RTT::OS::LowestPriority, RTT::OS::HighestPriority and RTT::OS::IncreasePriority variables which are defined for each OS.

OS's that support multiple schedulers can use the setScheduler function to influence the scheduling policy of a given thread. Orocos guarantees that the ORO_SCHED_RT and ORO_SCHED_OTHER variables are defined and can be used portably. The former `hints' a real-time scheduling policy, while the latter `hints' a not real-time secheduling policy. Each OS may define additional variables which map more appropriately to its scheduler policies. When only one scheduling policy is available, both variables map to the same scheduler.

4.2.4. ThreadScope: Oscilloscope Monitoring of Orocos Threads

You can configure the OS package using the configtool to report thread execution as block-waves on the parallel port or any other digital output device. Monitoring through the parallel port requires that a parallel port Device Driver is installed, and for Linux based OS'es, that you execute the Orocos program as root.

If the CoreLib Logger is active, it will log the mapping of Threads to the device's output pins to the orocos.log file. Just before step() is entered, the pin will be set high, and when step() is left, the pin is set low again. From within any (CoreLib) task, you may then additionally use the ThreadScope driver as such :

  DigitalOutInterface* pp = DigitalOutInterface::nameserver.getObject("ThreadScope");
if ( pp )
    pp->setBit( this->getTask()->thread()->threadNumber(), value );

which sets the corresponding bit to a boolean value. The main thread claims pin zero, the other pins are assigned incrementally as each new Orocos thread is created.

4.3. Synchronisation Primitives

Orocos OS only provides a few synchronisation primitives, mainly for guarding critical sections.

4.3.1. Mutexes

There are two kinds of Mutexes : Mutex and MutexRecursive. To lock a mutex, it has a method lock(), to unlock, the method is unlock() and to try to lock, it is trylock(). A lock() and trylock() on a recursive mutex from the same thread will always succeed, otherwise, it blocks.

For ease of use, there is a MutexLock which gets a Mutex as argument in the contstructor. As long as the MutexLock object exists, the given Mutex is locked. This is called a scoped lock.

Example 6.1. Locking a Mutex

The first listing shows a complete lock over a function :

  Mutex m;
  void foo() {
     int i;
     MutexLock lock(m);
     // m is locked.
     // ...
  } // when leaving foo(), m is unlocked.  

Any scope is valid, so if the critical section is smaller than the size of the function, you can :

  Mutex m;
  void bar() {
     int i;
     // non critical section
        MutexLock lock(m);
        // m is locked.
        // critical section
     } //  m is unlocked.
     // non critical section

4.3.2. Signals and Semaphores

Orocos provides a C++ semaphore abstraction class Semaphore. It is used mainly for non periodic, blocking tasks or threads. The higher level Event implementation in CoreLib can be used for thread safe signalling and data exchange in periodic tasks.

  Semaphore sem(0); // initial value is zero.
  void foo() {
     // Wait on sem, decrement value (blocking ):
     // awake : another thread did signal().

     // Signal sem, increment value (non blocking):

     // try wait on sem (non blocking):
     bool result = sem.trywait();
     if (result == false ) {
         // sem.value() was zero
     } else {
         // sem.value() was non-zero and is now decremented.

4.3.3. Compare And Swap ( CAS )

CAS is a fundamental building block of the CoreLib package for inter-thread communication and must be implemented for each OS target. See the Lock-Free sections of the CoreLib manual for Orocos classes which use this primitive.

Chapter 7. Hardware Device Interfaces


This document provides a short introduction to the Orocos Hardware Device Interface definitions. These are a collection of classes making abstraction of interacting with hardware components.

1. The Orocos Device Interface (DI)

Designing portable software which should interact with hardware is very hard. Some efforts, like Comedi propose a generic interface to communicate with a certain kind of hardware (mainly analog/digital IO). This allows us to change hardware and still use the same code to communicate with it. Therefore, we aim at supporting every Comedi supported card. We invite you to help us writing a C++ wrapper for this API and port comedilib (which adds more functionality) to the realtime kernels.

We do not want to force people into using Comedi, and most of us have home written device drivers. To allow total implementation independence, we are writing C++ device interfaces which just defines which functionalities a generic device driver should implement. It is up to the developers to wrap their C device driver into a class which implements this interface. You can find an example of this in the devices package. This package only contains the interface header files. Other packages should always point to these interface files and never to the real drivers actually used. It is up to the application writer to decide which driver will actually be used.

STRUCTURE The Device Interface can be structured in two major parts : physical device interfaces and logical device interfaces. Physical device interfaces can be subdivided in four basic interfaces: Analog Input, Analog Output, Digital Input, Digital Output. The major difference is that analog devices are addressed with a channel as parameter and write a ranged value, while digital devices are addressed with a bit number as parameter and a true/false value. Logical device interfaces represent the entities humans like to work with: a drive, a sensor, an encoder, etc. They put semantics on top of the physical interfaces they use underneath. You just want to know the position of a positional encoder in radians for example. Often, the physical layer is device dependent (and thus non-portable) while the logical layer is device independent.

Figure 7.1. Device Interface Overview

Device Interface Overview

EXAMPLE An example of the interactions between the logical and the physical layer is the logical encoder with its physical counting card. An encoder is a physical device keeping track of the position of an axis of a robot or machine. The programmer wishes to use the encoder as a sensor and just asks for the current position. Thus a logical encoder might choose to implement the SensorInterface which provides a read(ReadType & ) function. Upon construction of the logical sensor, we supply the real device driver as a parameter. This device driver implements for example AnalogInInterface which provides read(ReadType & data, unsigned int chan) and allows to read the position of a certain encoder of that particular card. Of course, we could also put a simulation of an encoder in place of the device driver for testing purposes.

2. The Device Interface Classes

The most common used interfaces for machine control are already implemented and tested on multiple setups. All the Device Interface classes reside in the RTT namespace.

2.1. Physical IO

There are several classes for representing different kinds of IO. Currently there are:

Table 7.1. Physical IO Classes

AnalogInInterfaceReading analog input channels
AnalogOutInterfaceWriting analog output channels
DigitalInInterfaceReading digital bits
DigitalOutInterfaceWriting digital bits
CounterInterfaceNot implemented yet
EncoderInterfaceA position/turn encoder

2.2. Logical Device Interfaces

From a logical point of view, the generic SensorInterface<T> is an easy to use abstraction for reading any kind of data of type T.

The Device Interface packages does however not provide implementations and thus the logical devices are implemented in the Device Driver package and RTT namespace. Examples are Axis, DigitalInput, DigitalOutput and AnalogDrive.

3. Porting Device Drivers to Device Interfaces

The methods in each interface are well documented and porting existing drivers (which mostly have a C API) to these should be quite straightforward. It is the intention that the developer writes a class that inherits from one or more interfaces and implements the corresponding methods. Logical Devices can then use these implementations to provide higher level functionalities.

4. Interface Name Serving

Name Serving is introduced in the Orocos CoreLib documentation.

The Device Interface provides name serving on interface level. This means that one can ask a certain interface by which objects it is implemented and retrieve the desired instance. No type-casting whatsoever is needed for this operation. For now, only the physical device layer can be queried for entities, since logical device drivers are typically instantiated where needed, given an earlier loaded physical device driver.

Example 7.1, “Using the name service” shows how one could query the AnalogOutInterface.

Example 7.1. Using the name service

unsigned int pos;
new FancyCard("CardName"); // FancyCard implements AnalogOutInterface
AnalogOutInterface* card = AnalogOutInterface::nameserver.getObject("CardName");
card->read(pos, 0);    // Read some data
delete card;