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A collection of robotics simulation environments for reinforcement learning

License: Other

Shell 0.13% Python 99.65% Dockerfile 0.21%

gymnasium-robotics-hysr's Introduction

Details and documentation on these robotics environments are available in OpenAI's blog post and the accompanying technical report.

If you use these environments, please cite the following paper:

@misc{1802.09464,
  Author = {Matthias Plappert and Marcin Andrychowicz and Alex Ray and Bob McGrew and Bowen Baker and Glenn Powell and Jonas Schneider and Josh Tobin and Maciek Chociej and Peter Welinder and Vikash Kumar and Wojciech Zaremba},
  Title = {Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research},
  Year = {2018},
  Eprint = {arXiv:1802.09464},
}

Fetch environments

FetchReach-v0: Fetch has to move its end-effector to the desired goal position.

FetchSlide-v0: Fetch has to hit a puck across a long table such that it slides and comes to rest on the desired goal.

FetchPush-v0: Fetch has to move a box by pushing it until it reaches a desired goal position.

FetchPickAndPlace-v0: Fetch has to pick up a box from a table using its gripper and move it to a desired goal above the table.

Shadow Dexterous Hand environments

HandReach-v0: ShadowHand has to reach with its thumb and a selected finger until they meet at a desired goal position above the palm.

HandManipulateBlock-v0: ShadowHand has to manipulate a block until it achieves a desired goal position and rotation.

HandManipulateEgg-v0: ShadowHand has to manipulate an egg until it achieves a desired goal position and rotation.

HandManipulatePen-v0: ShadowHand has to manipulate a pen until it achieves a desired goal position and rotation.

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