ManiSkill3: A Unified Benchmark for Generalizable Manipulation Skills
Reason this release was yanked:
missing a dependency in setup.py
Project description
ManiSkill is a powerful unified framework for robot simulation and training powered by SAPIEN. The entire stack is as open-source as possible and ManiSkill v3 is in beta release now. Among its features include:
- GPU parallelized visual data collection system. On the high end you can collect RGBD + Segmentation data at 20k FPS with a 4090 GPU, 10-100x faster compared to most other simulators.
- Example tasks covering a wide range of different robot embodiments (quadruped, mobile manipulators, single-arm robots) as well as a wide range of different tasks (table-top, locomotion, dextrous manipulation)
- GPU parallelized tasks, enabling incredibly fast synthetic data collection in simulation
- GPU parallelized tasks support simulating diverse scenes where every parallel environment has a completely different scene/set of objects
- Flexible task building API that abstracts away much of the complex GPU memory management code
Please refer our documentation to learn more information.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mani_skill-3.0.0b1.tar.gz
(87.3 MB
view hashes)
Built Distribution
Close
Hashes for mani_skill-3.0.0b1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8f92da550dfcfca23c511dc903fbdead4c00fc5d8db8ee53ebaacbda0dd6b019 |
|
MD5 | 7c69282005a990524811e61f00764c00 |
|
BLAKE2b-256 | 11ef6b1f53fa06b189f3c77cb3b622c06b7202c2ee763562c7f602ca40191184 |