This repo contains some novel robot simulators with PyBullet with Gym environments for training RL agents.
First install the dependencies for the suite,
pip install -r --user requirements/requirements.txt
The training examples in the examples/
directory use
Hydra and my implementation of
SAC. To run these training examples, you can install their
dependencies with
pip install -r --user requirements/examples.txt
Then, you may install the robot suite with
python setup.py install --user
This installs two packages, brs_data
and brs_envs
; the former containing the robot definitions,
and the latter containing the Gym environments. If you simply wish to use the environments (as
opposed to developing new ones), you only need to concern yourself with the brs_envs
package.
You can execute a training run with
python examples/rocket_lander.py
The examples/rocket_lander.py
script is configured by examples/config-rocket-lander.yaml
using
Hydra. You may tune some hyperparameters there or via the command line, for example
python examples/rocket_lander.py training.steps=50000 \
agent.params.max_replay_capacity=100000 \
agent.params.env_kwargs.max_pitch_offset=0.1