PKU-MARL/DexterousHands
A bimanual dexterous hand manipulation environment built on NVIDIA Isaac Gym for training deep reinforcement learning policies.
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Bi-DexHands provides a collection of bimanual dexterous manipulation simulation tasks integrated with reinforcement learning algorithms. It leverages NVIDIA Isaac Gym to enable running thousands of parallel environments on a single GPU, significantly accelerating RL training. The library supports both visual and low-level state observations, integrates with rl-games for training, and is used for research into achieving human-level hand dexterity and bimanual coordination in robotic systems.
Frequently asked
- What is PKU-MARL/DexterousHands?
- A bimanual dexterous hand manipulation environment built on NVIDIA Isaac Gym for training deep reinforcement learning policies.
- Is DexterousHands open source?
- Yes — PKU-MARL/DexterousHands is open source, released under the Apache-2.0 license.
- What language is DexterousHands written in?
- PKU-MARL/DexterousHands is primarily written in Python.
- How popular is DexterousHands?
- PKU-MARL/DexterousHands has 1.1k stars on GitHub.
- Where can I find DexterousHands?
- PKU-MARL/DexterousHands is on GitHub at https://github.com/PKU-MARL/DexterousHands.