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LFMC-PyVal

A Python based deployment repository for executing policies trained with LFMC-Gym. It can be used with both PyBullet and RaisimPy. Switching between the two engines is extremely simple.

Project website: https://ori-drs.github.io/lfmc/ </br>

Training repository: https://github.com/ori-drs/lfmc_gym </br> Deployment (C++): https://github.com/ori-drs/lfmc_cval </br>

Manuscript

Preprint: https://arxiv.org/abs/2209.14887

@article{lfmc-locomotion,
  title = {Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion},
  author = {Gangapurwala, Siddhant and Campanaro, Luigi and Havoutis, Ioannis},
  url = {https://arxiv.org/abs/2209.14887},
  publisher = {arXiv},  
  year = {2022},
  doi = {10.48550/ARXIV.2209.14887},
}

Prerequisites

This is optional and is only applicable if you would like to use RaisimPy. Ensure that you have compiled it and that $PYTHONPATH contains the RaisimPy install location.

export PYTHONPATH=$PYTHONPATH:<raisim-install-directory>/lib

Clone

To clone lfmc_pyval, use the following command. The Python version does not depend on other repositories.

git clone git@github.com:ori-drs/lfmc_pyval.git

Install

A setup.py script is provided with the Python package which handles all the necessary dependencies. It is recommended that you use a virtual environment.

If python3-venv is not already installed, use the following command.

sudo apt-get install python3-venv

Now create and source a virtual environment.

cd lfmc_pyval
python3 -m venv venv
source venv/bin/activate

The dependencies can then be installed by

pip install -e .

This will install numpy, torch, pybullet, and pyyaml along with their dependencies.

Execute

To run the included example, just use the following command.

python scripts/command_tracking.py

This will execute the locomotion policy in PyBullet. To switch to RaisimPy, simply edit the first line in the simulation configuration file. The file is called simulation.yaml and can be found at $LFMC_PYVAL_PATH/configuration/simulation.yaml. By default, this is what Line 1 reads.

engine: pybullet # Options: [raisim, pybullet]

To switch to Raisim, change it to

engine: raisim # Options: [raisim, pybullet]

Assuming RaisimUnity has been launched for visualization, you can execute the command_tracking.py script just as before. The example will now utilize the Raisim engine.

python scripts/command_tracking.py

Code Structure

└── common                          # Utilities used by modules throughout the project
    ├── paths.py                    # Utility to handle project related paths
    ├── networks.py                 # Contains MLP and GRU classes based on PyTorch
└── configuration                   # Configuration files
    ├── simulation.yaml             # Simulation configuration parameters
└── motion_control                  # Locomotion controller related files
    ├── controller.py               # Controller interface class
└── resources                       # Assets used in the project
    ├── models                      # Robot URDFs
    ├── parameters                  # Network parameters for locomotion and actuation
└── scripts                         # Python scripts
    ├── command_tracking.py         # Example script for executing command tracking policy
└── simulation                      # Simution utilities
    ├── actuation.py                # Contains the actuator network class for ANYmal C
    ├── pybullet.py                 # Interface utility for PyBullet
    ├── raisim.py                   # Interface utility for RaisimPy
    ├── wrapper.py                  # Wrapper to switch between PyBullet and RaisimPy
└── setup.py                        # Installs LFMC-PyVal and dependencies

Author(s)

Siddhant Gangapurwala