Article

Active Perception of Upper-Limb Functional Mobility Through Human-Robot Handovers

This study formulates upper-limb functional mobility estimation as an active perception problem, parameterizing reductions in healthy joint limits with impairment coefficients and integrating this into a human model used during robot interaction. The authors propose an online active perception pipeline in which the robot actively probes the user through repeated handover requests while progressively updating a Bayesian belief over the impairment coefficients. Simulation studies and a proof of concept on a robotic platform show that the pipeline can recover the impairment coefficients with relatively high accuracy in real human-robot handovers.

Part of the event: Active Perception of Upper-Limb Range of Motion via Robot Object Handovers

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