rc-a1

Unitree A1 simulation and control

Description

This is a controller subroutine for running MPC and RQL.

Requirements

The package is supposed to be run with the special QuadSDK branch (just install in our own docker image).

Usage

• Launch the simulation with:

roslaunch quad_utils quad_gazebo.launch

• Stand the robot with:

rostopic pub /robot_1/control/mode std_msgs/UInt8 "data: 1"

• Run MPC or RQL:

rosrun rql_mpc main.py

• Run the stack with twist input:

roslaunch quad_utils quad_plan_calf.launch reference:=twist 
rosrun teleop_twist_keyboard teleop_twist_keyboard.py cmd_vel:=/robot_1/cmd_vel

MPC, RQL Tuning:

To run MPC

In main.py

Uncomment ActorMPCA1 and past in controller instead of ActorRQLA1. dont forget to set is_fixed_critic_weights=True. (The critic model formally in the controller but not utilised by MPC, so critic weights update is not necessary)

Tune parameters:

• "QandR": - objective weights
• "final_time": - simulation end time
• "prediction_horizon": - N

To run RQL

In main.py

Uncomment ActorRQLA1 and past in controller instead of ActorMPCA1. dont forget to set is_fixed_critic_weights=False.

Tune parameters:

• "QandR": - objective weights
• "final_time": - simulation end time
• "prediction_horizon": - N

In critic model.

• single_weight_min= min model weights.
• single_weight_max= max model weights. In critic
• data_buffer_size= experience replay
• batch_size= batch sizes taken in experience replay
• td_n= number of temporal diffs if critic update
• critic_regularization_param= number that force remain weights the same (the higher number makes model more conservative)