rl_on_manifold
rl_on_manifold copied to clipboard
Robot Reinforcement Learning on the Constraint Manifold
Acting on the Tangent Space of the Constraint Manifold
Implementation of "Robot Reinforcement Learning on the Constraint Manifold"
Install
pip install -e .
Run Examples
cd examples
CircularMotion Environment.
Environment options [A, E, T], algorithms options [TRPO, PPO, SAC, DDPG, TD3]
python circle_exp.py --render --env A --alg TRPO
PlanarAirHockey Environment.
Environment options [H, D, UH, UD], algorithms options [TRPO, PPO, SAC, DDPG, TD3]
python planar_air_hockey_exp.py --debug-gui --env H --alg SAC
IiwaAirHockey Environment.
Environment options [7H, RMP], algorithms options [TRPO, PPO, SAC, DDPG, TD3]
python iiwa_air_hockey_exp.py --debug-gui --env 7H --alg SAC
CollisionAvoidance Environment.
Environment options [C], algorithms options [TRPO, PPO, SAC, DDPG, TD3]
python collision_avoidance_exp.py --render --env C --alg SAC
Bibtex
@inproceedings{CORL_2021_Learning_on_the_Manifold,
author = "Liu, P. and Tateo D. and Bou-Ammar, H. and Peters, J.",
year = "2021",
title = "Robot Reinforcement Learning on the Constraint Manifold",
booktitle = "Proceedings of the Conference on Robot Learning (CoRL)",
key = "robot learning, constrained reinforcement learning, safe exploration",
}