Influence of task decision autonomy on physical ergonomics and robot performances in an industrial human–robot collaboration scenario

Matteo Pantano, Qiaoyue Yang, Adrian Blumberg, Raven Reisch, Tobias Hauser, Benjamin Lutz, Daniel Regulin, Tobias Kamps, Konstantinos Traganos, Dongheui Lee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Adoption of human–robot collaboration is hindered by barriers in collaborative task design. A new approach for solving these problems is to empower operators in the design of their tasks. However, how this approach may affect user welfare or performance in industrial scenarios has not yet been studied. Therefore, in this research, the results of an experiment designed to identify the influences of the operator’s self-designed task on physical ergonomics and task performance are presented. At first, a collaborative framework able to accept operator task definition via parts’ locations and monitor the operator’s posture is presented. Second, the framework is used to tailor a collaborative experience favoring decision autonomy using the SHOP4CF architecture. Finally, the framework is used to investigate how this personalization influences collaboration through a user study with untrained personnel on physical ergonomics. The results from this study are twofold. On one hand, a high degree of decision autonomy was felt by the operators when they were allowed to allocate the parts. On the other hand, high decision autonomy was not found to vary task efficiency nor the MSD risk level. Therefore, this study emphasizes that allowing operators to choose the position of the parts may help task acceptance and does not vary operators’ physical ergonomics or task efficiency. Unfortunately, the test was limited to 16 participants and the measured risk level was medium. Therefore, this study also stresses that operators should be allowed to choose their own work parameters, but some guidelines should be followed to further reduce MSD risk levels.

Original languageEnglish
Article number943261
JournalFrontiers Robotics AI
Volume9
DOIs
StatePublished - 27 Sep 2022
Externally publishedYes

Keywords

  • autonomy
  • human-robot collaboration (HRC)
  • musculoskeletal disorders
  • physical ergonomics
  • RULA

Fingerprint

Dive into the research topics of 'Influence of task decision autonomy on physical ergonomics and robot performances in an industrial human–robot collaboration scenario'. Together they form a unique fingerprint.

Cite this