ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
Reason this release was yanked:
bug with demo_scenes.py code and one of the scene builders. Fixed in future versions
Project description
ManiSkill2 is a unified benchmark for learning generalizable robotic manipulation skills powered by SAPIEN. It features 20 out-of-box task families with 2000+ diverse object models and 4M+ demonstration frames. Moreover, it empowers fast visual input learning algorithms so that a CNN-based policy can collect samples at about 2000 FPS with 1 GPU and 16 processes on a workstation. The benchmark can be used to study a wide range of algorithms: 2D & 3D vision-based reinforcement learning, imitation learning, sense-plan-act, etc.
Please refer our documentation to learn more information.
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