Imposing Motion Variability for Ergonomic Human-Robot Collaboration
Mark Zolotas, Rui Luo, Salah Bazzi, Dipanjan Saha, Katiso Mabulu, Kristian Kloeckl, Taşkın Padır
- Year
- 2024
- Citations
- 5
- Access
- Open access
Abstract
OCCUPATIONAL APPLICATIONS"Overassistive" robots can adversely impact long-term human-robot collaboration in the workplace, leading to risks of worker complacency, reduced workforce skill sets, and diminished situational awareness. Ergonomics practitioners should thus be cautious about solely targeting widely adopted metrics for improving human-robot collaboration, such as user trust and comfort. By contrast, introducing variability and adaptation into a collaborative robot's behavior could prove vital in preventing the negative consequences of overreliance and overtrust in an autonomous partner. This work reported here explored how instilling variability into physical human-robot collaboration can have a measurably positive effect on ergonomics in a repetitive task. A review of principles related to this notion of "stimulating" robot behavior is also provided to further inform ergonomics practitioners of existing human-robot collaboration frameworks.
Keywords
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