An Empirical Study of Wrist-Target Construction and Joint-Angle Limits in Humanoid Arm Retargeting

Abstract:Motion retargeting maps a demonstrated human movement onto a robot to compute its joint motion. This study examines how the construction of the desired wrist position affects whether computed arm joint angles reach their permitted limits on a Unitree H1-2. A reconstructed target is formed from demonstrated arm directions and robot segment lengths, so its shoulder-to-wrist distance depends on the demonstrated angle between the segments even when no posture-matching preference is applied. A reach-normalized target retains that direction while rescaling the distance, using the same processed demonstrations and the same joint-angle method. Across a forward-reach sweep the reconstructed target places a joint angle at a bound in 10 of 20 repetitions and the reach-normalized target in none. Across 25 recordings from one participant the corresponding counts are 8 and 6 on the reaching arm and 14 and 5 on the supporting arm, and a second participant repeats the bricklaying and lifting comparison. In hardware replay a joint is commanded to a bound in 12 of 16 direction-matching arm-records and in none of the 16 normalized records, and within the eligible records both tracking error and executed torque at those frames exceed their values elsewhere in the same run. Cross-body reach and arm-to-arm clearance identify limits of radial adjustment. The findings support treating target construction and posture matching as separate retargeting decisions, and evaluating both alongside the wrist positions and clearance that manipulation requires.

Robotics (cs.RO)

arXiv:2610.37801 [cs.RO]

(or arXiv:2610.37801v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.37801 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.