[Submitted on 3 Oct 2026]
Title:Physical Twins: Accelerating and Enabling Robot Learning with Phantom Platforms
View a PDF of the paper titled Physical Twins: Accelerating and Enabling Robot Learning with Phantom Platforms, by Elizabeth Peiros and 6 other authors
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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.
Comments: 8 pages, 7 figures
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2610.06929 [cs.RO]
(or arXiv:2610.06929v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2610.06929
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Elizabeth Peiros [view email] [v1] Sat, 3 Oct 2026 01:10:27 UTC (11,068 KB)
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