In the demos folder a set of Simulink examples with various implementations is located. Feel free to experiment, adjust them and expand them to fit your project needs!
After opening, double clicking on any of the simulink models a set of parameters will be loaded automatically in the workspace.
The Simulink models are delivered in R2019a version. They will convert automatically to your Matlab version when you try to save the model.
The robot_ip is set to 172.16.0.2 by default after loading the demos. Make sure that the robot_ip parameters matches your setup, either by modifying it in the demos/demos_common_config.m matlab script file or from the cmd line after the simulink demo is loaded, like:
>> robot_ip = <your robot ip string>
At this point we can start the building & deployment of the Simulink model.
The current workflow presented is utilizing the “Run on Custom Hardware” Simulink App, present in Matlab versions \(\geq\) R2020a. In case of Matlab 2019a you can build the model normally by using the “Build Model” button. You then need to run the executable from a terminal as described below.
Let’s start by selecting the Run on custom hardware App from the Apps pane in Simulink.
Before executing make sure that the brakes of the robot are disengaged and that the robot is in execution mode!
You can then select from the Hardware tab either Monitor & Tune in case monitoring through the external mode is desired or Build, Deploy & Start for just executing the application without monitoring.
For running the generated executable manually from a terminal make sure that you’ve first exported the full libfranka build path, in case of Linux:
>> $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<libfranka build folder full path>
or in case of Windows, that you’ve included the full path of libfranka build directory in the PATH environment variable.
As a reminder, in case of a robot with system version 4.2.0 or greater, the FCI control mode needs to be explicitly enabled through Desk –> Sidebar menu –> Activate FCI.
The robot will move! Make sure that you are monitoring the situation, ready to take action if necessary!
You can then run the executable, which is located in the current working space.
In case of Linux:
or in case of Windows:
You can manually choose the simple tcpip from the Simulink model settings.
Automatic error recovery
If the robot encounters an error state and transitions to reflex mode, you may attempt to recover by executing the franka_automatic_error_recovery command in Matlab.
>> franka_automatic_error_recovery(<robot ip string>);
In case the command fails and the robot remains in the erroneous state try using the guiding mode to manually bring back the robot to a valid configuration.
Checkout the matlab library for a set of helper functions that can help to optimize your workflow.