Introduction

In this example, you configure a model to generate C++ code for a standalone ROS node. You then build and run the ROS node on an Ubuntu® Linux® system.

Prerequisites

Configure a Model for Code Generation

Configure a model to generate C++ code for a standalone ROS node. The model is the proportional controller introduced in theFeedback Control of a ROS-Enabled Robotexample.

Configure the Connection to the ROS Device

AROS deviceis any Linux system that has ROS installed and is capable of building and running a ROS node. If you have Simulink Coder, you can generate code for a standalone ROS node. If your system is connected to a ROS device, Simulink can also transfer the generated code to the ROS device, build an executable, and run the resulting ROS node (this is referred to as "deploying" the ROS node).

In this task, you decide if you want to generate code for the ROS node or if you want to build and run it on a ROS device. If you are connected to a ROS device, you can configure Simulink to use it as a deployment target for your ROS node.

ROS Folderis the location of the ROS installation on the ROS device. If you do not specify this folder, the settings test (see next step) tries to determine the correct folder for you.

The connection settings are not specific to a single model, but apply to all ROS models in Simulink.

Generate the C++ ROS Node

Generate code for a standalone ROS node, and automatically transfer, build, and run it on the ROS device. Exercise the generated ROS node using a ROS master running on the ROS device.

1.In MATLAB®, change the current folder to a temporary location where you have write permission.

2.The code generation process first prepares the model for simulation to ensure that all blocks are properly initialized. This preparation requires a valid connection to a ROS master.

In MATLAB, you can use therosdeviceobject to start a ROS master on the ROS device. If you provide no arguments,rosdeviceuses the device connection settings you entered in the Simulink dialog to connect to the ROS device.

d = rosdevice runCore(d);

3.Userosinitto connect MATLAB to the ROS master running on the ROS device:

rosinit(d.DeviceAddress)

4.Tell Simulink to use the same ROS connection settings as MATLAB. Under theSimulationtab, inPreparesection, selectROS Network。Set the ROS Master (ROS 1) and Node Host network addresses toDefault。

You only have to execute steps 2 - 4 once per MATLAB session, not every time you generate a ROS node.

5.Under theROStab, clickDeploy > Build & Run。If you get any errors about bus type mismatch, close the model, clear all variables from the base MATLAB workspace, and re-open the model.

Click on theView Diagnosticslink at the bottom of the model toolbar to see the output of the build process.

6.Once the code generation completes, the ROS node is transferred to the Catkin workspace on your ROS device. The node builds there and starts to run automatically in a synchronous fashion based on the sample time of the model.

The generated node connects to the ROS master running on the ROS device.

7.Userosnodeto list all running nodes is the ROS network. "robotcontroller" should be in the displayed list of nodes.

rosnodelist

You can userostopicto verify that the deployed node publishes data on the ROS topic to control the robot motion:

rostopicinfo/mobile_base/commands/velocity

运行and Verify the ROS Node

运行the newly-built ROS node and verify its behavior using a MATLAB-based robot simulator.

1.In MATLAB, typeExampleHelperSimulinkRobotROSto start the Robot Simulator. The simulator automatically connects to the ROS master running on the ROS device. If you want to connect to a Gazebo-based robot simulation, seeConnect to a ROS-enabled Robot from Simulink®。

sim = ExampleHelperSimulinkRobotROS

2.Verify that the simulated robot moves toward the goal (theDesired Positionconstant specified in the model). The robot stops once it reaches the goal [-10, 10].

3.ClickReset Simulationto reset the robot's position to [0, 0]. The robot starts to move immediately towards the goal position.

4.In MATLAB, you can manage ROS nodes generated by Simulink with therosdeviceobject. Once a Simulink model is deployed, you can userosdevice在任何p运行和停止节点oint, without having to rebuild it in Simulink.

TheAvailableNodesproperty shows the deployed robotcontroller node. You can verify that the node is running by calling theisNodeRunningfunction.

d = rosdevice

isNodeRunning(d,'robotcontroller')

5.Stop the ROS node from running.

stopNode(d,'robotcontroller') isNodeRunning(d,'robotcontroller')

6.Click theReset Simulationbutton in the simulation window. The robot stays at location [0,0] and does not move.

runNode(d,'robotcontroller')

7.Once you are done verifying, you can clean up the system state as follows.

stopNode(d,'robotcontroller')

rosshutdown

Advanced Topics and Troubleshooting

Specify ROS network settings in Simulink: By default, Simulink uses the ROS connection settings fromrosinitin MATLAB. To override these settings, specify ROS connection settings in Simulink. Under theSimulationtab, inPreparesection, selectROS Networkand set the ROS Master and Node Host network addresses:

指定外部ROS包依赖关系:指定外部ROS包依赖to the generated ROS node, specify appropriate toolchain options. In the Configuration parameters, underCode Generation > Toolchain Settings, specify theBuild configurationasSpecifyfrom the drop-down. Then, you can specify theRequired Packages, Include Directories, Link Libraries, Library PathsandDefinesbased on the external ROS packages that you wish to integrate with the generated ROS node.

Generated C++ code archive: No matter whatBuild action您选择(没有,构建和加载、构建和运行),Simulink always generates two files in your current folder: an archive containing the C++ source code (RobotController.tgz in our example) and a shell script for extracting and building the C++ code manually (build_ros_model.sh). If your MATLAB computer is not connected to the ROS device, you can transfer the files manually and build them there.

Processor-specific generated code: If you use blocks from other products (such as Computer Vision System Toolbox™), the generated code may include processor-specific optimizations that lead to compilation problems when building the ROS node on Linux. In these cases, you need to let Simulink know the platform on which the generated code is compiled. You can do this through theHardware Implementationpane of the Model Configuration Parameters dialog.

运行ning ROS Master in MATLAB: In the example above, you connected to a ROS master running on the ROS device. Alternatively, you can create a ROS master in MATLAB. Userosinitat the MATLAB command line:

rosinit('NodeHost', )

For example, if the IP address of your host computer is 172.18.250.92, use the following command:

rosinit('NodeHost','172.18.250.92')

TheNodeHostsetting is important to ensure that the generated ROS node is able to communicate to the master on MATLAB.Note: The generated ROS node will use theNodeHostIP address to communicate to the global ROS node in MATLAB, so ensure that the specified IP address is accessible from the ROS device (for example, usingping). See theConnect to a ROS Networkexample for more details on the significance of theNodeHostsetting.

Tasking mode: Simulink can generate code for either multi-tasking or single-tasking modes (seeTime-Based Scheduling and Code Generation(Simulink Coder)). By default, generated ROS code uses single-tasking mode (a single thread for all the rates) without real-time scheduling. This allows the generated ROS code to execute withoutsudoprivileges, but can lead to less predictable performance.

If you require more predictable performance, you can configure the model to use multi-tasking. In theSolverpane of the Configuration Parameters dialog enableTreat each discrete rate as a separate taskto enable multi-tasking. In generated code, this creates a separate thread for each rate in the model and uses prioritized scheduling for the threads.

To run the ROS node, you need to have administrative privileges on the ROS device. Simulink automatically detects if your privileges are insufficient when the model is deployed to the target device.