Damping profile learning for human-robot collaboration using Bayesian optimization with a task success rate model

In the realm of human-robot collaboration, impedance and admittance control are widely utilized techniques to regulate the interaction dynamics between humans and robots. This study proposes a novel approach to enhance the performance of human-robot collaboration by adapting the damping profile used...

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Bibliografische Detailangaben

Hauptverfasser:	Liem Duc TRAN, Tasuku YAMAWAKI, Masahito YASHIMA
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	The Japan Society of Mechanical Engineers 2025-04-01
Schriftenreihe:	Mechanical Engineering Journal
Schlagworte:	human-robot collaboration admittance control variable impedance learning bayesian optimization
Online-Zugang:	https://www.jstage.jst.go.jp/article/mej/12/3/12_24-00483/_pdf/-char/en
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