Consideration of ergonomic aspects in human-robot task allocation methods

Abstract

Human Robot Collaboration (HRC) has opened opportunities of task sharing between human and robots under an open workspace in manufacturing environment. Traditional task sharing philosophy in human robot teams have followed the leftover approach, where human is assigned task which are difficult for robot to perform. Contemporary research is now increasingly centered on developing flexible and adaptive task allocation strategies that ensure equitable sharing. However, majority of the algorithms present today still lack the focus on overall human well-being. The aim of this work is to consider human factors in task allocation. It addresses this in three folds: first addressing the task analysis and assignment that includes a thorough study of the factors to be considered for task allocation and the methodology used. The factors for analysis range in the focus from human, robot, process, and production perspective. Secondly, visualizing the task allocation strategy using digital tool Ema Work designer and finally the evaluation framework for ergonomics. This study therefore develops an algorithm and evaluation method designed to consider human factors in task allocation. The evaluation framework was tested on a ski assembly process, showcasing comparison of the ergonomic evaluation: physical and cognitive in two different case scenarios. Physical ergonomics details on the Ergonomic Assessment Worksheet (EAWS) score pertaining to load, posture, and repositioning score. The cognitive ergonomics framework defines a Mental Workload Index (MWLI) considering task demand, level of performance, level of resources, level of information processing, and level of decision making.