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DexSuite: An All-in-One Framework for Dexterous Manipulation Across Arms, Hands, and Tasks
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First announced by arXiv: 2026-10-30 · Indexed by Pub-AI: 2026-10-30 UTC
DexSuite: An All-in-One Framework for Dexterous Manipulation Across Arms, Hands, and Tasks
First announced by arXiv: 2026-10-30 · Original record ↗
- arxiv
- 2610.37799
Explicit source versions (1)
- v1 · Date not supplied
- Preprint available
Source date: 2026-10-30 · First detected: 2026-10-30 UTC · Historical baseline
Source evidence (1)
- Official evidence ↗ · RSS guid=oai:arXiv.org:2610.37799v1; arxiv:announce_type=new; item pubDate (official metadata)
Abstract · arxiv
Human-level dexterity remains a central open problem in robotics, yet few simulation frameworks cover the full workflow of dexterous manipulation, from setting up a robot to collecting dexterous demonstrations and evaluating policies. We present DexSuite, an all-in-one simulation framework for dexterous manipulation built on the Genesis simulator. DexSuite provides 30 tasks and assembles its 10 arms and 12 end-effectors, from parallel-jaw grippers to dexterous hands, into more than 100 single-arm robots and thousands of bimanual pairs. It also ships a standardized environment API, integrated teleoperation, and simulated tactile sensing. Moreover, we define a benchmark of 16 task-embodiment pairs spanning diverse contact complexities and horizons, and release a dataset of 4,700 successful episodes in simulation from human teleoperation, scripted experts, and learned policies. We release DexSuite as open source and hope others will build on it. Videos and datasets are available at https://dexsuiteorg.github.io