Further development (bug fixes, new features etc) happen in the master branch. The 'paper' branch of this repository contains the original code accompanying the paper:
"Learning Agile Robotic Locomotion Skills by Imitating Animals",
by Xue Bin Peng et al. It provides a Gym environment for training a simulated quadruped robot to imitate various reference motions, and example training code for learning the policies.
Project page: https://xbpeng.github.io/projects/Robotic_Imitation/index.html
- Install MPC extension (Optional)
python3 setup.py install --user
Install dependencies:
- Install MPI:
sudo apt install libopenmpi-dev
- Install requirements:
pip3 install -r requirements.txt
and it should be good to go.
To train a policy, run the following command:
python3 motion_imitation/run.py --mode train --motion_file motion_imitation/data/motions/dog_pace.txt --int_save_freq 10000000 --visualize
--mode
can be eithertrain
ortest
.--motion_file
specifies the reference motion that the robot is to imitate.motion_imitation/data/motions/
contains different reference motion clips.--int_save_freq
specifies the frequency for saving intermediate policies every n policy steps.--visualize
enables visualization, and rendering can be disabled by removing the flag.- the trained model and logs will be written to
output/
.
For parallel training with MPI run:
mpiexec -n 8 python3 motion_imitation/run.py --mode train --motion_file motion_imitation/data/motions/dog_pace.txt --int_save_freq 10000000
-n
is the number of parallel.
To test a trained model, run the following command
python3 motion_imitation/run.py --mode test --motion_file motion_imitation/data/motions/dog_pace.txt --model_file motion_imitation/data/policies/dog_pace.zip --visualize
--model_file
specifies the.zip
file that contains the trained model. Pretrained models are available inmotion_imitation/data/policies/
.
motion_imitation/data/motions/
contains different reference motion clips.motion_imitation/data/policies/
contains pretrained models for the different reference motions.
For more information on the reference motion data format, see the DeepMimic documentation
Disclaimer: This is not an official Google product.