COGNITIVE WORKLOAD ANALYSIS IN COLLABORATIVE ROBOTIC PROGRAMMING OF MANUFACTURING ASSEMBLIES USING TEACH PENDANTS

Document Type

Conference Proceeding

Publication Date

1-1-2025

Abstract

In automated manufacturing assembly operations, collaborative robots (cobots) conduct the task of automating repetitive and precise activities to allow human workers to concentrate on more intricate and decision-oriented tasks.Programming cobots for assembly tasks often requires manually setting and recording specific positions throughout the assembly process utilizing the native teach pendant, which is referred to as teach point programming. However, teach point programming can be laborious and introduce physical strain and cognitive challenges due to ergonomic issues and complex, non-intuitive teach pendant interfaces. This study aims to assess how cognitive workload in teach point programming impacts user task performance. To achieve this, we recruited 28 participants to perform standardized assembly tasks on a designated task board. During the experiment, the task success rates, completion times, and cognitive workload (using the NASA Task Load Index (NASA-TLX), a widely recognized tool for assessing perceived workload) were recorded. Correlation analysis revealed significant relationships between cognitive workload and task success. Specifically, higher task success was associated with lower physical and cognitive workload and reduced perceived effort. Additionally, participants who achieved greater task success reported higher levels of perceived performance. In contrast, cognitive workload factors including perceived mental demand, temporal demand, and frustration did not exhibit a direct correlation with task success. None of the cognitive workload responses were correlated with task completion times, indicating that cognitive stress may not influence task speed. The results were further supported by analyzing physical robot-only ratings, gender distributions, and pre-task experience. These findings underscore the importance of cognitive load in achieving successful task outcomes and established a human-centric understanding of teach point programming in cobots. In addition, this study provides an avenue of future research where addressing the relevant cognitive factors could potentially enhance overall task performance in manufacturing environments andleadtomoreeffectivehuman-robotcollaborationinassembly tasks.

Publication Title

Proceedings of ASME 2025 20th International Manufacturing Science and Engineering Conference Msec 2025

ISBN

[9780791889022]

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