Modalities of sequential human robot collaboration trigger different modifications of trunk oscillations.

biomechanical risk collaborative robotics ergonomics inertial measurement unit movement analysis

Journal

Frontiers in neurorobotics
ISSN: 1662-5218
Titre abrégé: Front Neurorobot
Pays: Switzerland
ID NLM: 101477958

Informations de publication

Date de publication:
2023
Historique:
received: 09 03 2023
accepted: 05 06 2023
medline: 10 7 2023
pubmed: 10 7 2023
entrez: 10 7 2023
Statut: epublish

Résumé

Human robot collaboration is quickly gaining importance in the robotics and ergonomics fields due to its ability to reduce biomechanical risk on the human operator while increasing task efficiency. The performance of the collaboration is typically managed by the introduction of complex algorithms in the robot control schemes to ensure optimality of its behavior; however, a set of tools for characterizing the response of the human operator to the movement of the robot has yet to be developed. Trunk acceleration was measured and used to define descriptive metrics during various human robot collaboration strategies. Recurrence quantification analysis was used to build a compact description of trunk oscillations. The results show that a thorough description can be easily developed using such methods; moreover, the obtained values highlight that, when designing strategies for human robot collaboration, ensuring that the subject maintains control of the rhythm of the task allows to maximize comfort in task execution, without affecting efficiency.

Identifiants

pubmed: 37425334
doi: 10.3389/fnbot.2023.1183164
pmc: PMC10323748
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1183164

Informations de copyright

Copyright © 2023 Ranaldi, Bibbo, Corvini, Schmid and Conforto.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Simone Ranaldi (S)

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Daniele Bibbo (D)

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Giovanni Corvini (G)

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Maurizio Schmid (M)

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Silvia Conforto (S)

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Classifications MeSH