Abstract

Occupational applications Since cobots (collaborative robots) are increasingly being introduced in industrial environments, being aware of their potential positive and negative impacts on human collaborators is essential. This study guides occupational health workers by identifying the potential gains (reduced perceived time demand, number of gestures and number of errors) and concerns (the cobot takes a long time to perceive its environment, which leads to an increased completion time) associated with working with cobots. In our study, the collaboration between human and cobot during an assembly task did not negatively impact perceived cognitive load, increased completion time (but decreased perceived time demand), and decreased the number of gestures performed by participants and the number of errors made. Thus, performing the task in collaboration with a cobot improved the user’s experience and performance, except for completion time, which increased. This study opens avenues to investigate how to improve cobots to ensure the usability of the human-machine system at work. Technical Background: Industry 4.0 implements smart technologies to increase productivity and to decrease the associated risks. Using cobots is considered by industry as a potential means to reduce physical constraints and improve performance without having to replace the human factor. Research has yet to prove these benefits on humans. Purpose: The goal of this study was to determine if working with a cobot improved perceived cognitive load of an operator and the usability of the system. Methods: Participants replicated three construction models using Duplos. Approximatively half of our participants (n = 32) accomplished the task alone and the other half accomplished the same task with a cobot (n = 22). We then used the NASA TLX to measure workload and, through a sub-dimension, perceived cognitive load. Completion time (for each model), number of errors (placing and replacing a piece), and the number of gestures (movements of the upper limbs) were also measured. Results: Collaboration with a cobot led to significantly fewer gestures (51 vs. 74), fewer errors (2 vs. 8), and reduced perceived time demand, but increased completion time (136 vs. 55 s). Perceived cognitive load was not impacted by the cobot (36 vs. 37). Conclusion: We conclude that collaboration with a cobot adapting to human variability is possible, and that it could lead to better performance and could improve certain dimensions of system usability.

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