Multi-Objective Multi-Resource Task Allocation For Collaborative Robots Systems

The shift from Industry 4.0 to Industry 5.0 has led to a greater focus on workers' needs in the workplace. Collaborative robots have been introduced to promote a fair division of tasks and reduce physical and mental strain on workers. However, there is a lack of research on how to implement human- centered task allocation. This study proposes a model for multiobjective task allocation, including minimizing makespan, energy expenditure, and mental workload. The study also suggests a method for evaluating mental workload. Results show that the strictness of task sequence affects makespan and energy expenditure, and a new constraint related to idle times is proposed. The optimal level of worker saturation is one that minimizes makespan while minimizing increases in energy expenditure and mental workload. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)