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Learning Human-like Hand Reaching for Human-Robot Handshaking

Vignesh Prasad; Ruth Stock-Homburg; Jan Peters
In: IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation (ICRA-2021), May 30 - June 5, Xi'an, China, Pages 3612-3618, IEEE, 2021.


One of the first and foremost non-verbal interactions that humans perform is a handshake. It has an impact on first impressions as touch can convey complex emotions. This makes handshaking an important skill for the repertoire of a social robot. In this paper, we present a novel framework for learning reaching behaviours for human-robot handshaking behaviours for humanoid robots solely using third-person human-human interaction data. This is especially useful for non-backdrivable robots that cannot be taught by demonstrations via kinesthetic teaching. Our approach can be easily executed on different humanoid robots. This removes the need for re-training, which is especially tedious when training with human-interaction partners. We show this by applying the learnt behaviours on two different humanoid robots with similar degrees of freedom but different shapes and control limits.

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