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

Abstract

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 multi-objective 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.