Paper Detail

Mana: Dexterous Manipulation of Articulated Tools

Zhao-Heng Yin, Guanya Shi, Pieter Abbeel, C. Karen Liu

arxiv Score 13.3

Published 2026-06-11 · First seen 2026-06-13

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Abstract

Articulated tool manipulation remains a major challenge in dexterous robotics due to the need to coordinate internal degrees of freedom and contact-rich interactions. While prior work has largely focused on rigid objects, articulated tool use remains underexplored because of its physical complexity and the difficulty of learning functional grasping and manipulation policies. We present Mana (Manipulation Animator), a general sim-to-real framework that reinterprets dexterous manipulation as an animation problem. Inspired by computer animation, Mana employs a coarse-to-fine pipeline that transforms procedurally-generated grasp keyframes into manipulation trajectories through motion planning and reinforcement learning. The data generation process is largely automatic, requiring only a few mouse clicks to specify functional affordances (<1 minute per tool). Across four articulated tools spanning different scales and joint types, Mana achieves zero-shot sim-to-real transfer for both grasping and in-hand manipulation, demonstrating a scalable approach to dexterous articulated tool use.

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BibTeX

@article{yin2026mana,
  title = {Mana: Dexterous Manipulation of Articulated Tools},
  author = {Zhao-Heng Yin and Guanya Shi and Pieter Abbeel and C. Karen Liu},
  year = {2026},
  abstract = {Articulated tool manipulation remains a major challenge in dexterous robotics due to the need to coordinate internal degrees of freedom and contact-rich interactions. While prior work has largely focused on rigid objects, articulated tool use remains underexplored because of its physical complexity and the difficulty of learning functional grasping and manipulation policies. We present Mana (Manipulation Animator), a general sim-to-real framework that reinterprets dexterous manipulation as an an},
  url = {https://arxiv.org/abs/2606.13677},
  keywords = {cs.RO, cs.AI, cs.CV, cs.LG, Affordance, Artificial intelligence, GRASP, Computer science, Process (computing)},
  eprint = {2606.13677},
  archiveprefix = {arXiv},
}

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