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DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation
Published in IROS 2026, arxiv, 2025
We introduce perioperation, a paradigm for robotic data collection that sensorizes and records human manipulation while maximizing the transferability of the data to real robots. We implement this paradigm in DEXOP, a passive hand exoskeleton designed to maximize human ability to collect rich sensory (vision + tactile) data for diverse dexterous manipulation tasks in natural environments. DEXOP mechanically connects human fingers to robot fingers, providing users with direct contact feedback and mirrors the human hand pose to the passive robot hand to maximize the transfer of demonstrated skills to the robot. The force feedback and pose mirroring make task demonstrations more natural for humans compared to teleoperation, increasing both speed and accuracy. Our project page is https://dex-op.github.io/
Recommended citation: Fang, H. S., Romero, B., Xie, Y., Hu, A., Huang, B. R., Alvarez, J., ... & Agrawal, P. (2025). Dexop: A device for robotic transfer of dexterous human manipulation. arXiv preprint arXiv:2509.04441
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Teaching experience 2
Workshop, University 1, Department, 2015
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Grader (18.404 Theory of Computation)
Undergraduate course, MIT 18.404 Theory of Computation, 2025
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