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This paper introduces a "physical twin" phantom device designed to facilitate real-world reinforcement learning testing for human-robot interaction algorithms without relying on human participants. By replicating complex shoulder mechanics and joint limits, the system addresses critical challenges in repeatability, scalability, and safety for physically interactive AI agents. The work represents a significant methodological advance in robotics research, enabling safer and more diverse experimentation for tasks like physical therapy and search and rescue.
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Physical Twins: Accelerating and Enabling Robot Learning with Phantom Platforms

arXiv2 min read

arXiv:2610.06929v1 Announce Type: new Abstract: Improvements in human-robot physical interaction (pHRI) can have major implications for physical therapy, search and rescue, and telemedicine. However, a major challenge concerns human constraints and safety in human-robot physical experiments. Concerns about human studies also include repeatability, scalability, and participant diversity. To conduct such experiments, an IRB and willing human participants are required. In this work, we present an improved phantom device, a physical twin, that enables real-world RL-type testing for physically interactive algorithms. The new device not only replicates the ball-and-socket motion of the shoulder but also renders scapular and protraction/retraction motions. The experiments showcase the device's ability to render multiple 3D joint limits and demonstrate a Franka Panda arm sensing limits and interacting with the device as an arm for ADLs (activities of daily living) and pHRI tasks.

Abstract:Improvements in human-robot physical interaction (pHRI) can have major implications for physical therapy, search and rescue, and telemedicine. However, a major challenge concerns human constraints and safety in human-robot physical experiments. Concerns about human studies also include repeatability, scalability, and participant diversity. To conduct such experiments, an IRB and willing human participants are required. In this work, we present an improved phantom device, a physical twin, that enables real-world RL-type testing for physically interactive algorithms. The new device not only replicates the ball-and-socket motion of the shoulder but also renders scapular and protraction/retraction motions. The experiments showcase the device's ability to render multiple 3D joint limits and demonstrate a Franka Panda arm sensing limits and interacting with the device as an arm for ADLs (activities of daily living) and pHRI tasks.

Robotics (cs.RO)

arXiv:2610.06929 [cs.RO]

(or arXiv:2610.06929v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.06929 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 224 words

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