ArticleSmart and sustainable manufacturing systems2022
Evaluation of Robot Degradation on Human-Robot Collaborative Performance in Manufacturing.
Article in Smart and sustainable manufacturing systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Human-robot collaborative systems are highly sought candidates for smart manufacturing applications because of their adaptability and consistency in production tasks. However, manufacturers are still hesitant to adopt these systems because of the lack of metrics regarding the influence of the degradation of collaborative industrial robots on human-robot teaming performance. Hence, this paper defines teaming performance metrics with respect to robot degradation. In addition, the defined metrics are applied to a human-robot collaborative inverse peg-in-hole case study with respect to the degradation of the joint angular encoder and current sensor. Specifically, this case study compares pure insertion versus insertion with spatial scanning to solve the peg-in-hole problem, and manual intervention is implemented in the event of robotic failure. The metrics used in the case study showed that pure insertion more sensitive to robot degradation with manual intervention was required at 0.04° as opposed to 0.12° from insertion with scanning. Therefore, insertion with scanning was shown to be more robust to robot degradation at the cost of a slower insertion time of 9.48 s compared to 3.19 s. Thus, this paper provides knowledge and usable metrics regarding the influence of robot degradation on human-robot collaborative systems in manufacturing applications.
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