Flexible and Adaptive Planning forHuman-Robot Interaction inSelf-Optimizing Assembly Cells

Abstract: Due to an increasing diversity of products in product space production systems have to react more flexible and dynamic. Thereby, the human operator must be seen as an integral part of the production process because on the one hand he/she has to supervise the machines and robots and on the other hand he/she has to take over individual operations that cannot be automated. For establishing a flexible planning process of assembly operations that satisfies also the ergonomic requirements of human-robot interaction a comprehensive Cognitive Simulation Model is presented consisting of a formerly developed Cognitive Control Unit (CCU) and a newly developed graph-based planner. The CCU is based on the popular architecture of human cognition Soar. The additional planner enables the CCU to consider more complex planning criteria regarding the whole assembly sequence. Therefore, the final product is decomposed to obtain all valid assembly sequences and transferred into a state graph. The edges are rated at runtime according to the activated procedural knowledge. A modified version of the search algorithm A*Prune is finally applied to find the best continuations for the current assembly sequence. The presented approach is validated by means of a simulation study. The results show that the human-robot cooperation can be improved significantly, for example, by reducing the number of strenuous manual interventions of the human operator.

Keywords: cognitive automation, human-robot cooperation, production planning

DOI: 10.54941/ahfe100461

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