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Deployment of Training Results

1. Deployment Environment Configuration

• Install ROS 2 Iron: Set up a ROS 2 Iron-based algorithm Development Environment on the Ubuntu 22.04 operating system. For installation, please refer to the documentation: https://docs.ros.org/en/iron/Installation/Ubuntu-Install-Debians.html, and choose "ros-iron-desktop" for installation. After the installation of ROS 2 Iron is completed, enter the following Shell commands in the Bash end point to install the libraries required by the Development Environment:

  sudo apt update
  sudo apt install ros-iron-urdf \
              ros-iron-urdfdom \
              ros-iron-urdfdom-headers \
              ros-iron-kdl-parser \
              ros-iron-hardware-interface \
              ros-iron-controller-manager \
              ros-iron-controller-interface \
              ros-iron-controller-manager-msgs \
              ros-iron-control-msgs \
              ros-iron-controller-interface \
              ros-iron-gazebo-* \
              ros-iron-rviz* \
              ros-iron-rqt-gui \
              ros-iron-rqt-robot-steering \
              ros-iron-plotjuggler* \
              ros-iron-control-toolbox \
              ros-iron-ros2-control \
              ros-iron-ros2-controllers \
              ros-dev-tools \
              cmake build-essential libpcl-dev libeigen3-dev libopencv-dev libmatio-dev \
              python3-pip libboost-all-dev libtbb-dev liburdfdom-dev liborocos-kdl-dev -y

• Install the onnxruntime dependency, download link:https://github.com/microsoft/onnxruntime/releases/tag/v1.10.0. Please choose the appropriate version to download according to your operating system and platform. For example, on Ubuntu 20.04 x86_64, please follow the steps below for installation:

  wget https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-linux-x64-1.10.0.tgz
  
  tar xvf onnxruntime-linux-x64-1.10.0.tgz
  
  sudo cp -a onnxruntime-linux-x64-1.10.0/include/* /usr/include
  sudo cp -a onnxruntime-linux-x64-1.10.0/lib/* /usr/lib

2. Create Workspace

You can create an RL deployment development workspace by following these steps:

• Open a Bash end point.

• Create a new directory to store the workspace. For example, you can create a directory named "limx_ws" under the user's home directory:

  mkdir -p ~/limx_ws/src

• Download the Motion Control Development Interface:

  cd ~/limx_ws/src
  git clone https://github.com/limxdynamics/limxsdk-lowlevel.git

• Download Gazebo Simulator:

  cd ~/limx_ws/src
  git clone https://github.com/limxdynamics/tron1-gazebo-ros2.git

• Download the robot model description file

  cd ~/limx_ws/src
  git clone https://github.com/limxdynamics/robot-description.git

• Download Visualization Tool

  cd ~/limx_ws/src
  git clone https://github.com/limxdynamics/robot-visualization.git

• Download RL deployment source code:

  cd ~/limx_ws/src
  git clone https://github.com/limxdynamics/tron1-rl-deploy-ros2.git

• Compile Project:

  cd ~/limx_ws
  source /opt/ros/iron/setup.bash
  colcon build --cmake-args -DCMAKE_BUILD_TYPE=Release

• Select robot type

  • List available robot types via the Shell command tree -L 1 src/robot-description/pointfoot :

    src/robot-description/pointfoot
    ├── PF_P441A
    ├── PF_P441B
    ├── PF_P441C
    ├── PF_P441C2
    ├── PF_TRON1A
    ├── SF_TRON1A
    └── WF_TRON1A
    

  • TakingPF_P441C (please replace it according to the actual robot type) as an example, set the robot model type:

    echo 'export ROBOT_TYPE=PF_P441C' >> ~/.bashrc && source ~/.bashrc
    

• Select training environment

  The currently supported training environments are isaacgym and isaaclab. Taking isaacgym as an example, set the training environment type:

  echo 'export RL_TYPE=isaacgym' >> ~/.bashrc && source ~/.bashrc
  

• Run Simulation

  source /opt/ros/iron/setup.bash
  source install/setup.bash
  ros2 launch robot_hw pointfoot_hw_sim.launch.py