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Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot - 2021

Research Area:  Machine Learning


This technical report presentspanda-gym, a set Reinforcement Learning (RL) environments for theFranka Emika Panda robot integrated with OpenAI Gym. Five tasks are included: reach, push, slide,pick & place and stack. They all follow a Multi-Goal RL framework, allowing to use goal-orientedRL algorithms. To foster open-research, we chose to use the open-source physics engine PyBullet.The implementation chosen for this package allows to define very easily new tasks or new robots.This report also presents a baseline of results obtained with state-of-the-art model-free off-policyalgorithms.

Author(s) Name:  Quentin Gallouédec, Nicolas Cazin, Emmanuel Dellandréa, Liming Chen

Journal name:  A Preprint

Conferrence name:  

Publisher name:  arXiv:2106.13687v1


Volume Information:  25 Jun 2021

Paper Link:   arXiv:2106.13687v1