Data-driven Grip Force Variation in Robot-Human Handovers

2023/03/28 by Khanna, Parag, Björkman, Mårten, Smith, Christian
#FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Robotics (cs.RO)

paper · doi:10.48550/arxiv.2303.16009

Abstract

Handovers frequently occur in our social environments, making it imperative for a collaborative robotic system to master the skill of handover. In this work, we aim to investigate the relationship between the grip force variation for a human giver and the sensed interaction force-torque in human-human handovers, utilizing a data-driven approach. A Long-Short Term Memory (LSTM) network was trained to use the interaction force-torque in a handover to predict the human grip force variation in advance. Further, we propose to utilize the trained network to cause human-like grip force variation for a robotic giver.

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