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Toward safe and high-performance human–robot collaboration via implementation of redundancy and understanding the effects of admittance term parameters

Published online by Cambridge University Press:  15 November 2021

Mert Kanık ,
Orhan Ayit Open the ORCID record for Orhan Ayit [Opens in a new window] ,
Mehmet Ismet Can Dede Open the ORCID record for Mehmet Ismet Can Dede [Opens in a new window]  and
Enver Tatlicioglu Open the ORCID record for Enver Tatlicioglu [Opens in a new window]
Mert Kanık
Affiliation:
Biomedical Engineering Department, New Jersey Institute of Technology, Newark, NJ, USA
Orhan Ayit
Affiliation:
Department of Mechanical Engineering, Izmir Institute of Technology, Izmir, Turkey
Mehmet Ismet Can Dede*
Affiliation:
Department of Mechanical Engineering, Izmir Institute of Technology, Izmir, Turkey
Enver Tatlicioglu
Affiliation:
Department of Electrical and Electronics Engineering, Ege University, Izmir, Turkey
*
*Corresponding author. E-mail: [email protected]
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Summary

Today, demandsin industrial manufacturing mandate humans to work with large-scale industrial robots, and this collaboration may result in dangerous conditions for humans. To deal with this situation, this work proposes a novel approach for redundant large-scale industrial robots. In the proposed approach, an admittance controller is designed to regulate the interaction between the end effector of the robot and the human. Additionally, an obstacle avoidance algorithm is implemented in the null space of the robot to prevent any possible unexpected collision between the human and the links of the robot. After safety performance of this approach is verified via simulations and experimental studies, the effect of the parameters of the admittance controller on the performance of collaboration in terms of both accuracy and total human effort is investigated. This investigation is carried out via 8 experiments by the participation of 10 test subjects in which the effect of different admittance controller parameters such as mass and damper are compared. As a result of this investigation, tuning insights for such parameters are revealed.

Keywords

collaborative robothuman–robot interactionadmittance controlobstacle avoidanceredundancy resolution
Type
Research Article
Information
Robotica , Volume 40 , Issue 7 , July 2022 , pp. 2112 - 2127
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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