linerobot/dashboard

Line Following Robot Dashboard

This folder contains all the source files to validly run the Python dashboard for visualizing the Line Following Robot (LFR) Digital Shadow (DS).

It is important that ROS2 is enabled in the environment that runs the main code. This will also enable the rclpy module.

Properties

This dashboard does the following things:

1. It reads a depth image from ROS2 and displays it using the bone colormap.
2. It analyzes the depth image in order to identify the robot's state (position and heading). This information is transferred to another ROS2 connection.
3. The sensor data is read and visualized in a history plot.
4. The robot states (both the system under study and the model) are read from ROS2 and visualized in the plot (if they exist).

How to Compile

For the dashboard to work, it is required that the lfr_msgs package for ROS2 communication is compiled. This package is located inside the ros2 folder. In order to compile, execute the following steps.

1. Open a clean environment (i.e., terminal, powershell...). For Windows, this must be a Visual Studio Command Prompt to allow for compilation.
2. Make sure ROS2 is enabled by sourcing the global setup or local_setup script. This is presumably located in the /opt/ folder.
3. Execute one of the following commands in the ros2 folder (choose which one applies):
   Windows: colcon build --merge-install --packages-select lfr_msgs
   Linux/Mac OS: colcon build --packages-select lfr_msgs

How to Run

1. Open a clean environment (i.e., terminal, powershell...). This may be the same environment as used for the compilation.
2. Enable ROS2 (and the lfr_msgs package) by sourcing the setup or local_setup script from ros2/install. You may need to compile this package in the ros2 directory first (see above).
3. Launch the main.py script from the environment.