A Control Approach for Human-Robot Ergonomic Payload Lifting

Lorenzo Rapetti; Carlotta Sartore; Mohamed Elobaid; Yeshasvi Tirupachuri; Francesco Draicchio; Tomohiro Kawakami; Takahide Yoshiike; Daniele Pucci

doi:10.1109/ICRA48891.2023.10161454

A Control Approach for Human-Robot Ergonomic Payload Lifting

Lorenzo Rapetti, Carlotta Sartore, Mohamed Elobaid, Yeshasvi Tirupachuri, Francesco Draicchio, Tomohiro Kawakami, Takahide Yoshiike, Daniele Pucci

Fondazione Istituto Italiano di Tecnologia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control approach for human-robot collaboration based on human monitoring through whole-body wearable sensors, and interaction modelling through coupled rigid-body dynamics. Moreover, a trajectory advancement strategy is proposed, allowing for online adaptation of the robot trajectory depending on the human motion. The resulting framework allows us to perform payload lifting tasks, taking into account the ergonomic requirements of the agents. Validation has been performed in an experimental scenario using the iCub3 humanoid robot and a human subject sensorized with the iFeel wearable system.

Original language	English
Title of host publication	Proceedings - ICRA 2023
Subtitle of host publication	IEEE International Conference on Robotics and Automation
Publisher	IEEE
Pages	7504-7510
Number of pages	7
ISBN (Electronic)	9798350323658
DOIs	https://doi.org/10.1109/ICRA48891.2023.10161454
Publication status	Published - 2023
Event	2023 IEEE International Conference on Robotics and Automation, ICRA 2023 - London, United Kingdom Duration: 29 May 2023 → 2 Jun 2023

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2023-May
ISSN (Print)	1050-4729

Conference

Conference	2023 IEEE International Conference on Robotics and Automation, ICRA 2023
Country/Territory	United Kingdom
City	London
Period	29/05/23 → 2/06/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICRA48891.2023.10161454

Cite this

Rapetti, L., Sartore, C., Elobaid, M., Tirupachuri, Y., Draicchio, F., Kawakami, T., Yoshiike, T., & Pucci, D. (2023). A Control Approach for Human-Robot Ergonomic Payload Lifting. In Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation (pp. 7504-7510). (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2023-May). IEEE. https://doi.org/10.1109/ICRA48891.2023.10161454

@inproceedings{27009d909dba47ae971e59ecdd65feb3,

title = "A Control Approach for Human-Robot Ergonomic Payload Lifting",

abstract = "Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control approach for human-robot collaboration based on human monitoring through whole-body wearable sensors, and interaction modelling through coupled rigid-body dynamics. Moreover, a trajectory advancement strategy is proposed, allowing for online adaptation of the robot trajectory depending on the human motion. The resulting framework allows us to perform payload lifting tasks, taking into account the ergonomic requirements of the agents. Validation has been performed in an experimental scenario using the iCub3 humanoid robot and a human subject sensorized with the iFeel wearable system.",

author = "Lorenzo Rapetti and Carlotta Sartore and Mohamed Elobaid and Yeshasvi Tirupachuri and Francesco Draicchio and Tomohiro Kawakami and Takahide Yoshiike and Daniele Pucci",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Robotics and Automation, ICRA 2023 ; Conference date: 29-05-2023 Through 02-06-2023",

year = "2023",

doi = "10.1109/ICRA48891.2023.10161454",

language = "English",

series = "Proceedings - IEEE International Conference on Robotics and Automation",

publisher = "IEEE",

pages = "7504--7510",

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Rapetti, L, Sartore, C, Elobaid, M, Tirupachuri, Y, Draicchio, F, Kawakami, T, Yoshiike, T & Pucci, D 2023, A Control Approach for Human-Robot Ergonomic Payload Lifting. in Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. Proceedings - IEEE International Conference on Robotics and Automation, vol. 2023-May, IEEE, pp. 7504-7510, 2023 IEEE International Conference on Robotics and Automation, ICRA 2023, London, United Kingdom, 29/05/23. https://doi.org/10.1109/ICRA48891.2023.10161454

A Control Approach for Human-Robot Ergonomic Payload Lifting. / Rapetti, Lorenzo; Sartore, Carlotta; Elobaid, Mohamed et al.
Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. IEEE, 2023. p. 7504-7510 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2023-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Control Approach for Human-Robot Ergonomic Payload Lifting

AU - Rapetti, Lorenzo

AU - Sartore, Carlotta

AU - Elobaid, Mohamed

AU - Tirupachuri, Yeshasvi

AU - Draicchio, Francesco

AU - Kawakami, Tomohiro

AU - Yoshiike, Takahide

AU - Pucci, Daniele

PY - 2023

Y1 - 2023

N2 - Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control approach for human-robot collaboration based on human monitoring through whole-body wearable sensors, and interaction modelling through coupled rigid-body dynamics. Moreover, a trajectory advancement strategy is proposed, allowing for online adaptation of the robot trajectory depending on the human motion. The resulting framework allows us to perform payload lifting tasks, taking into account the ergonomic requirements of the agents. Validation has been performed in an experimental scenario using the iCub3 humanoid robot and a human subject sensorized with the iFeel wearable system.

AB - Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control approach for human-robot collaboration based on human monitoring through whole-body wearable sensors, and interaction modelling through coupled rigid-body dynamics. Moreover, a trajectory advancement strategy is proposed, allowing for online adaptation of the robot trajectory depending on the human motion. The resulting framework allows us to perform payload lifting tasks, taking into account the ergonomic requirements of the agents. Validation has been performed in an experimental scenario using the iCub3 humanoid robot and a human subject sensorized with the iFeel wearable system.

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DO - 10.1109/ICRA48891.2023.10161454

M3 - Conference contribution

AN - SCOPUS:85168671449

T3 - Proceedings - IEEE International Conference on Robotics and Automation

SP - 7504

EP - 7510

BT - Proceedings - ICRA 2023

PB - IEEE

T2 - 2023 IEEE International Conference on Robotics and Automation, ICRA 2023

Y2 - 29 May 2023 through 2 June 2023

ER -

A Control Approach for Human-Robot Ergonomic Payload Lifting

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