Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

Giuseppe Averta; Visar Arapi; Antonio Bicchi; Cosimo della Santina; Matteo Bianchi

doi:10.1007/978-3-030-71356-0_9

Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

Giuseppe Averta^*, Visar Arapi, Antonio Bicchi, Cosimo della Santina, Matteo Bianchi

^*Corresponding author for this work

Learning & Autonomous Control

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

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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.

Original language	English
Title of host publication	Human-Friendly Robotics 2020
Subtitle of host publication	Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020)
Editors	Matteo Saveriano, Erwan Renaudo, Antonio Rodríguez-Sánchez, Justus Piater
Publisher	Springer
Pages	116-126
ISBN (Electronic)	978-3-030-71356-0
ISBN (Print)	978-3-030-71355-3
DOIs	https://doi.org/10.1007/978-3-030-71356-0_9
Publication status	Published - 2021
Event	HFR 2020: 13th International Workshop on Human-Friendly Robotics - Innsbruck, Austria Duration: 1 Oct 2020 → 2 Oct 2020

Publication series

Name	Springer Proceedings in Advanced Robotics
Volume	18
ISSN (Print)	2511-1256
ISSN (Electronic)	2511-1264

Workshop

Workshop	HFR 2020: 13th International Workshop on Human-Friendly Robotics
Country/Territory	Austria
City	Innsbruck
Period	1/10/20 → 2/10/20

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Human motor control
Human-like robotic movements
Learning from humans
Machine learning

Access to Document

10.1007/978-3-030-71356-0_9

Averta2021_Chapter_ModelingHumanMotorSkillsToEnhaFinal published version, 3 MB

Cite this

Averta, G., Arapi, V., Bicchi, A., Santina, C. D., & Bianchi, M. (2021). Modeling Human Motor Skills to Enhance Robots’ Physical Interaction. In M. Saveriano, E. Renaudo, A. Rodríguez-Sánchez, & J. Piater (Eds.), Human-Friendly Robotics 2020: Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020) (pp. 116-126). (Springer Proceedings in Advanced Robotics; Vol. 18). Springer. https://doi.org/10.1007/978-3-030-71356-0_9

Averta, Giuseppe ; Arapi, Visar ; Bicchi, Antonio et al. / Modeling Human Motor Skills to Enhance Robots’ Physical Interaction. Human-Friendly Robotics 2020: Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020). editor / Matteo Saveriano ; Erwan Renaudo ; Antonio Rodríguez-Sánchez ; Justus Piater. Springer, 2021. pp. 116-126 (Springer Proceedings in Advanced Robotics).

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abstract = "The need for users{\textquoteright} 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.",

keywords = "Human motor control, Human-like robotic movements, Learning from humans, Machine learning",

author = "Giuseppe Averta and Visar Arapi and Antonio Bicchi and Santina, {Cosimo della} and Matteo Bianchi",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; HFR 2020: 13th International Workshop on Human-Friendly Robotics ; Conference date: 01-10-2020 Through 02-10-2020",

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Averta, G, Arapi, V, Bicchi, A, Santina, CD & Bianchi, M 2021, Modeling Human Motor Skills to Enhance Robots’ Physical Interaction. in M Saveriano, E Renaudo, A Rodríguez-Sánchez & J Piater (eds), Human-Friendly Robotics 2020: Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020). Springer Proceedings in Advanced Robotics, vol. 18, Springer, pp. 116-126, HFR 2020: 13th International Workshop on Human-Friendly Robotics, Innsbruck, Austria, 1/10/20. https://doi.org/10.1007/978-3-030-71356-0_9

Modeling Human Motor Skills to Enhance Robots’ Physical Interaction. / Averta, Giuseppe; Arapi, Visar; Bicchi, Antonio et al.
Human-Friendly Robotics 2020: Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020). ed. / Matteo Saveriano; Erwan Renaudo; Antonio Rodríguez-Sánchez; Justus Piater. Springer, 2021. p. 116-126 (Springer Proceedings in Advanced Robotics; Vol. 18).

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

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T1 - Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

AU - Averta, Giuseppe

AU - Arapi, Visar

AU - Bicchi, Antonio

AU - Santina, Cosimo della

AU - Bianchi, Matteo

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Human motor control

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KW - Learning from humans

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SN - 978-3-030-71355-3

T3 - Springer Proceedings in Advanced Robotics

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EP - 126

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A2 - Saveriano, Matteo

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PB - Springer

T2 - HFR 2020: 13th International Workshop on Human-Friendly Robotics

Y2 - 1 October 2020 through 2 October 2020

ER -

Averta G, Arapi V, Bicchi A, Santina CD, Bianchi M. Modeling Human Motor Skills to Enhance Robots’ Physical Interaction. In Saveriano M, Renaudo E, Rodríguez-Sánchez A, Piater J, editors, Human-Friendly Robotics 2020: Proceedings of the 13th International Workshop on Human-Friendly Robotics (HFR 2020). Springer. 2021. p. 116-126. (Springer Proceedings in Advanced Robotics). doi: 10.1007/978-3-030-71356-0_9

Modeling Human Motor Skills to Enhance Robots’ Physical Interaction

Abstract

Publication series

Workshop

Bibliographical note

Keywords

Access to Document

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