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Article

Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities

Intelligent Automation Centre, Wolfson School of Mechanical, Electrical, and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK
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Academic Editors: Juan Ernesto Solanes Galbis, Luis Gracia and Jaime Valls Miro
Electronics 2021, 10(13), 1509; https://doi.org/10.3390/electronics10131509
Received: 29 April 2021 / Revised: 15 June 2021 / Accepted: 17 June 2021 / Published: 22 June 2021
(This article belongs to the Special Issue Advances in Human-Machine Interaction and Robotics)
With collaborative robots and the recent developments in manufacturing technologies, physical interactions between humans and robots represent a vital role in performing collaborative tasks. Most previous studies have focused on robot motion planning and control during the execution of the task. However, further research is required for direct physical contact for human-robot or robot-robot interactions, such as co-manipulation. In co-manipulation, a human operator manipulates a shared load with a robot through a semi-structured environment. In such scenarios, a multi-contact point with the environment during the task execution results in a convoluted force/toque signature that is difficult to interpret. Therefore, in this paper, a muscle activity sensor in the form of an electromyograph (EMG) is employed to improve the mapping between force/torque and displacements in co-manipulation tasks. A suitable mapping was identified by comparing the root mean square error amongst data-driven models, mathematical models, and hybrid models. Thus, a robot was shown to effectively and naturally perform the required co-manipulation with a human. This paper’s proposed hypotheses were validated using an unseen test dataset and a simulated co-manipulation experiment, which showed that the EMG and data-driven model improved the mapping of the force/torque features into displacements. View Full-Text
Keywords: human-robot collaboration; human-human co-manipulation; data-driven modelling; mathematical modelling; object manipulation; impedance control human-robot collaboration; human-human co-manipulation; data-driven modelling; mathematical modelling; object manipulation; impedance control
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MDPI and ACS Style

Al-Yacoub, A.; Flanagan, M.; Buerkle, A.; Bamber, T.; Ferreira, P.; Hubbard, E.-M.; Lohse, N. Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities. Electronics 2021, 10, 1509. https://doi.org/10.3390/electronics10131509

AMA Style

Al-Yacoub A, Flanagan M, Buerkle A, Bamber T, Ferreira P, Hubbard E-M, Lohse N. Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities. Electronics. 2021; 10(13):1509. https://doi.org/10.3390/electronics10131509

Chicago/Turabian Style

Al-Yacoub, Ali, Myles Flanagan, Achim Buerkle, Thomas Bamber, Pedro Ferreira, Ella-Mae Hubbard, and Niels Lohse. 2021. "Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities" Electronics 10, no. 13: 1509. https://doi.org/10.3390/electronics10131509

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