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.