Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

Book chapter (2021)

Authors

Giuseppe Averta Istituto Italiano di Tecnologia, University of Pisa
Visar Arapi University of Pisa
Antonio Bicchi University of Pisa, Istituto Italiano di Tecnologia
C. Della Santina Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Matteo Bianchi University of Pisa
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2021 Giuseppe Averta, Visar Arapi, Antonio Bicchi, C. Della Santina, Matteo Bianchi
DOI
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https://doi.org/10.1007/978-3-030-71356-0_9
Machine learning Human motor control Human-like robotic movements Learning from humans
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Published Date

2021

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

The need for users’ safety and technology acceptability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions and interactions. In this manuscript, we present a research approach that moves from the understanding of human movements and derives usefull guidelines for the planning of arm movements and the learning of skills for physical interaction of robots with the surrounding environment.