Journal Article

Implementation and Evaluation of Dynamic Task Allocation for Human–Robot Collaboration in Assembly

Freitag, Michael, Vur, Burak, Sontopski, Marius, Niermann, Dario, Maack, Emily, Petzoldt, Christoph

2022

Overview

Human–robot collaboration is becoming increasingly important in industrial assembly. In view of high cost pressure, resulting productivity requirements, and the trend towards human-centered automation in the context of Industry 5.0, a reasonable allocation of individual assembly tasks to humans or robots is of central importance. Therefore, this article presents a new approach for dynamic task allocation, its integration into an intuitive block-based process planning framework, and its evaluation in comparison to both manual assembly and static task allocation. For evaluation, a systematic methodology for comprehensive assessment of task allocation approaches is developed, followed by a corresponding user study. The results of the study show for the dynamic task allocation on the one hand a higher fluency in the human–robot collaboration with good adaptation to process delays, and on the other hand a reduction in the cycle time for assembly processes with sufficiently high degrees of parallelism. Based on the study results, we draw conclusions regarding assembly scenarios in which manual assembly or collaborative assembly with static or dynamic task allocation is most appropriate. Finally, we discuss the implications for process planning when using the proposed task allocation framework.

• Publisher: MDPI AG
• Subject: assembly / Automation / Collaboration / collaborative robots / Cooperation / Flexibility / human-centricity / human–robot collaboration / industry 5.0 / Planning / Productivity / Robots / task allocation