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Physical Human–Robot Cooperation Based on Robust Motion Intention Estimation

Published online by Cambridge University Press:  23 September 2020

Konstantinos I. Alevizos ,
Charalampos P. Bechlioulis Open the ORCID record for Charalampos P. Bechlioulis [Opens in a new window]  and
Kostas J. Kyriakopoulos
Konstantinos I. Alevizos
Affiliation:
Control Systems Lab, School of Mechanical Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, Athens, 15780, Greece
Charalampos P. Bechlioulis*
Affiliation:
Control Systems Lab, School of Mechanical Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, Athens, 15780, Greece
Kostas J. Kyriakopoulos
Affiliation:
Control Systems Lab, School of Mechanical Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, Athens, 15780, Greece
*
*Corresponding author. E-mail: chmpechl@mail.ntua.gr
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Summary

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Cooperative transportation by human and robotic coworkers constitutes a challenging research field that could lead to promising technological achievements. Toward this direction, the present work demonstrates that, under a leader–follower architecture, where the human determines the object’s desired trajectory, complex cooperative object manipulation with minimal human effort may be achieved. More specifically, the robot estimates the object’s desired motion via a prescribed performance estimation law that drives the estimation error to an arbitrarily small residual set. Subsequently, the motion intention estimation is utilized in the object dynamics to determine the interaction force between the human and the object. Human effort reduction is then achieved via an impedance control scheme that employs the aforementioned estimations. The feedback relies exclusively on the robot’s force/torque, position as well as velocity measurements at its end effector, without incorporating any other information on the task. Moreover, an adaptive control scheme is adopted to relax the need for exact knowledge of the object dynamics. Finally, an extension for multiple robotic coworkers is studied and verified via simulation, while extensive experimental results for the single robot case clarify the proposed method and corroborate its efficiency.

Keywords

RAAD2018pHRICooperative transportationPrescribed performanceImpedance control
Type
Articles
Information
Robotica , Volume 38 , Special Issue 10: Human–Robot Interaction (HRI) , October 2020 , pp. 1842 - 1866
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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