I want to share our team’s recent work on isaacgym:
We present the RL-based dual dexterous hand environment, Bi-DexHands, which provides a collection of bimanual dexterous manipulations tasks and reinforcement learning algorithms for solving them. Reaching human-level sophistication of hand dexterity and bimanual coordination remains an open challenge for modern robotics researchers.
Bi-DexHands contains complex dexterous hands control tasks. Bi-DexHands is built in the NVIDIA Isaac Gym with a high-performance guarantee for training RL algorithms. Our environments focus on applying model-free RL/MARL algorithms for bimanual dexterous manipulation, which are considered as a challenging task for traditional control methods.
Please visit the github page for more details and examples: