Ergonomic human-robot collaboration in industry: A review
In the current industrial context, the importance of assessing and improving workers’ health conditions is widely recognised. Both physical and psycho-social factors contribute to jeopardising the underlying comfort and well-being, boosting the occurrence of diseases and injuries, and affecting thei...
Saved in:
Published in | Frontiers in robotics and AI Vol. 9; p. 813907 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
03.01.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | In the current industrial context, the importance of assessing and improving workers’ health conditions is widely recognised. Both physical and psycho-social factors contribute to jeopardising the underlying comfort and well-being, boosting the occurrence of diseases and injuries, and affecting their quality of life. Human-robot interaction and collaboration frameworks stand out among the possible solutions to prevent and mitigate workplace risk factors. The increasingly advanced control strategies and planning schemes featured by collaborative robots have the potential to foster fruitful and efficient coordination during the execution of hybrid tasks, by meeting their human counterparts’ needs and limits. To this end, a thorough and comprehensive evaluation of an individual’s ergonomics, i.e. direct effect of workload on the human psycho-physical state, must be taken into account. In this review article, we provide an overview of the existing ergonomics assessment tools as well as the available monitoring technologies to drive and adapt a collaborative robot’s behaviour. Preliminary attempts of ergonomic human-robot collaboration frameworks are presented next, discussing state-of-the-art limitations and challenges. Future trends and promising themes are finally highlighted, aiming to promote safety, health, and equality in worldwide workplaces. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 Reviewed by: Claudio Castellini, University of Erlangen Nuremberg, Germany Arto Reiman, University of Oulu, Finland This article was submitted to Human-Robot Interaction, a section of the journal Frontiers in Robotics and AI These authors have contributed equally to this work Edited by: Erin K. Chiou, Arizona State University, United States |
ISSN: | 2296-9144 2296-9144 |
DOI: | 10.3389/frobt.2022.813907 |