A Variational Approach to Minimum-Jerk Trajectories for Psychological Safety in Collaborative Assembly Stations

Abstract

Collaborative robotics is one of the main drivers of the fourth industrial revolution, where robots and humans cooperate in a shared workspace. Such robots are distinguished from the traditional robots by several features that, if tuned correctly, ensure safe physical interaction. However, interaction with robots also represents a potential source of psychological stress. Indeed, it has been proven that working and sharing the workspace with robots can psychologically stress the operator. This drawback-in addition to the reduced speed operation imposed by safety standards-represents a constraint difficult to bear for small and medium-sized enterprises. In this letter, we propose a novel trajectory-planning methodology for collaborative robots able to ensure both psychological and physical safety. We rely on the available literature and the calculus of variations to identify a family of psychologically acceptable minimum-jerk trajectories. From the identified family, we compute the fastest trajectory that limits the physical danger represented by the robot. A numerical implementation of the method is discussed, and experimental results prove the effectiveness of the idea.