Machines (Nov 2022)
Behavior Analysis for Increasing the Efficiency of Human–Robot Collaboration
Abstract
In this study, we proposed a behavior analysis for increasing the efficiency of human–robot collaboration in an assembly task. This study was inspired by previous research, in which a set of operator intentions in assembly was translated into an intention graph to formulate a probabilistic decision model for planning robot actions in the presence of operator intention ambiguity and perception uncertainty. Here, we achieved improvement by considering the analysis of human behavior in the form of fatigue and adaptation ability. We also switched the collaboration scheme from cooperative to collaborative, in which both the robot and operator work in parallel, not sequentially. We then tested the proposed method with chair assembly and the results indicated that shortening the assembly duration increased the effectiveness of the assembly process. The results also indicated that the proposed method for assembling 50 chairs was 4.68 s faster than the previous method.
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