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Communication Dans Un Congrès Année : 2013

Physical human-robot interaction in the handshaking case: learning of rhythmicity using oscillators neuron

Artem Melnyk
Patrick Henaff

Résumé

This paper presents experimental results on the learning of synchrony between human and a robot arm when they interact in a handshaking situation. The controller is based on two coupled nonlinear neurons (central pattern generator, CPG) that are able to learn to oscillate at different frequencies depending on a biological inspired learning mechanism. This mechanism uses interaction force measured in the robot joint as a learning signal. Results show that the CPG learns and follows the human rhythm easily and then enjoy it.
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Dates et versions

hal-00802019 , version 1 (18-03-2013)

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  • HAL Id : hal-00802019 , version 1

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Artem Melnyk, Viacheslav Khomenko, Vladimir Borysenko, Patrick Henaff. Physical human-robot interaction in the handshaking case: learning of rhythmicity using oscillators neuron. 2013 IFAC Conference on Manufacturing Modelling, Management, and Control, IFAC MIM '2013, Jun 2013, St Petersbourg, Russia. ⟨hal-00802019⟩
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