A framework for singularity-robust manipulator control during physical human-robot interaction

Abstract

Collaborative robot manipulators are being used to assist human workers performing physically intensive tasks. The finite reach of the manipulator often results in the robot being operated in proximity to kinematic singularity, negatively affecting the stability and performance of operation. Methods of controlling manipulators in the proximity of singularities and mitigating their effects on performance have been widely researched. However, little attention has been given to developing suitable methods for handling singularities specifically for applications where the manipulator physically interacts with a human operator. In these applications additional factors such as human comfort and interaction experience need to be considered. This work presents a framework for handling robotic singularities developed with the human operator in mind. Singularity robustness is achieved using a novel approach to dampen motion of the manipulator along singular directions. An exponential scaling shapes the damping to create a smooth behavior beneficial for physical human–robot interaction. The damping is applied asymmetrically depending on if the robot is heading towards or away from singular configurations, improving the interaction experience for the human operator. Additionally, bounded virtual forces are used to subtly guide the operator away from singular configurations. The proposed framework is validated in simulation and tested on an industrial manipulator.