24e8018e0d | ||
---|---|---|
.github/workflows | ||
src | ||
.gitattributes | ||
.gitignore | ||
.gitmodules | ||
LICENCE | ||
README.md | ||
README_CN.md |
README.md
rl_sar
Simulation verification and physical deployment of the quadruped robot's reinforcement learning algorithm. "sar" stands for "simulation and real".
Preparation
Clone the code (sync submodules)
git clone --recursive https://github.com/fan-ziqi/rl_sar.git
If there are updates:
git pull
git submodule update --remote --recursive
Dependency
Download and deploy libtorch
at any location
cd /path/to/your/torchlib
wget https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcpu.zip
unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cpu.zip -d ./
echo 'export Torch_DIR=/path/to/your/torchlib' >> ~/.bashrc
Install dependency packages
sudo apt install ros-noetic-teleop-twist-keyboard ros-noetic-controller-interface ros-noetic-gazebo-ros-control ros-noetic-joint-state-controller ros-noetic-effort-controllers ros-noetic-joint-trajectory-controller
Install yaml-cpp
git clone https://github.com/jbeder/yaml-cpp.git
cd yaml-cpp && mkdir build && cd build
cmake -DYAML_BUILD_SHARED_LIBS=on .. && make
sudo make install
sudo ldconfig
Install lcm
git clone https://github.com/lcm-proj/lcm.git
cd lcm && mkdir build && cd build
cmake .. && make
sudo make install
sudo ldconfig
Compilation
Customize the following two functions in your code to adapt to different models:
torch::Tensor forward() override;
torch::Tensor compute_observation() override;
Then compile in the root directory
cd ..
catkin build
Running
Before running, copy the trained pt model file to rl_sar/src/rl_sar/models/YOUR_ROBOT_NAME
, and configure the parameters in config.yaml
.
Simulation
Open a new terminal, launch the gazebo simulation environment
source devel/setup.bash
roslaunch rl_sar start_a1.launch
Open a new terminal, run the control program
source devel/setup.bash
rosrun rl_sar rl_sim
Open a new terminal, run the keyboard control program
rosrun teleop_twist_keyboard teleop_twist_keyboard.py
Physical Robots
Unitree A1
Unitree A1 can be connected using both wireless and wired methods:
- Wireless: Connect to the Unitree starting with WIFI broadcasted by the robot (Note: Wireless connection may lead to packet loss, disconnection, or even loss of control, please ensure safety)
- Wired: Use an Ethernet cable to connect any port on the computer and the robot, configure the computer IP as 192.168.123.162, and the gateway as 255.255.255.0
Open a new terminal and start the control program
source devel/setup.bash
rosrun rl_sar rl_real_a1
Press the R2 button on the controller to switch the robot to the default standing position, press R1 to switch to RL control mode, and press L2 in any state to switch to the initial lying position. The left stick controls x-axis up and down, controls yaw left and right, and the right stick controls y-axis left and right.
Cyberdog1
-
Connect to the robot (only need to do this once)
Connect the local PC to the Cyberdog's USB download Type-C interface (located in the middle) and wait for the "L4T-README" pop-up to appear.
ping 192.168.55.100 # IP assigned to the local PC ssh mi@192.168.55.1 # Log in to the NX application board, password 123 athena_version -v # Verify the current version is >=1.0.0.94
-
Enter motor control mode (only need to do this once)
Modify the configuration switch to activate user control mode and run the user's own controller:
ssh root@192.168.55.233 # Log in to the motion control board cd /robot ./initialize.sh # Copy factory code to the readable and writable development area (/mnt/UDISK/robot-software), switch to developer mode, only need to be executed once vi /mnt/UDISK/robot-software/config/user_code_ctrl_mode.txt # Switch mode: 1 (0: default mode, 1 user code control motor mode), reboot the robot to take effect
-
Use Ethernet cable to connect the computer and the motion control board
Due to the risk of damaging the interface and higher communication latency when using a Type-C connection, it is recommended to use an Ethernet cable for connection. Disconnect the cables between the main control and motion control board of the robot, and connect the computer and the motion control board directly with an Ethernet cable, then set the wired connection IPv4 of the computer to manual
192.168.55.100
. It is recommended to remove the head and lead the cable out of the head opening. Be careful not to damage the cables during disassembly and assembly.Initialize the robot's connection (this step needs to be done every time the robot is reconnected)
cd src/rl_sar/scripts bash init_cyberdog.sh
Start the control program
source devel/setup.bash rosrun rl_sar rl_real_cyberdog
Press 0 on the keyboard to switch the robot to the default standing position, press P to switch to RL control mode, and press 1 in any state to switch to the initial lying position. WS controls x-axis, AD controls yaw, and JL controls y-axis.
-
Use a Type-C cable to connect the computer and the robot
If it is inconvenient to disassemble the robot, a Type-C cable can be temporarily used for debugging. The procedure after connecting the Type-C cable is the same as above.
-
After using Ctrl+C to end the program, the robot's motion control program will automatically reset. If the program goes out of control, the motion control program can also be manually restarted.
Note: After restarting the motion control program, there is a startup time of approximately 5-10 seconds. During this time, running programs may report
Motor control mode has not been activated successfully
. Wait until there are no errors before running the control program again.cd src/rl_sar/scripts bash kill_cyberdog.sh
Add Your Robot
In the following, let ROBOT represent the name of your robot.
- Create a model package named ROBOT_description in the robots folder. Place the URDF model in the urdf path within the folder and name it ROBOT.urdf. Create a namespace named ROBOT_gazebo in the config folder within the model file for joint configuration.
- Place the model file in models/ROBOT.
- Add a new field in rl_sar/config.yaml named ROBOT and adjust the parameters, such as changing the model_name to the model file name from the previous step.
- Add a new launch file in the rl_sar/launch folder. Refer to other launch files for guidance on modification.
- Change ROBOT_NAME to ROBOT in rl_xxx.cpp.
- Compile and run.
- If the torque of your robot's joints exceeds 50Nm, you need to modify line 180 in
rl_sar/src/unitree_ros/unitree_legged_control/src/joint_controller.cpp
to:
This will remove the 50Nm limit.// calcTorque = computeTorque(currentPos, currentVel, servoCmd); calcTorque = servoCmd.posStiffness * (servoCmd.pos - currentPos) + servoCmd.velStiffness * (servoCmd.vel - currentVel) + servoCmd.torque;
Citation
Please cite the following if you use this code or parts of it:
@software{fan-ziqi2024rl_sar,
author = {fan-ziqi},
title = {{rl_sar: Simulation Verification and Physical Deployment of the Quadruped Robot's Reinforcement Learning Algorithm.}},
url = {https://github.com/fan-ziqi/rl_sar},
year = {2024}
}