Manipulator performance constraints in Cartesian admittance control for human-robot cooperation

Abstract

This paper addresses the problem of providing feedback to the operator about the manipulator's performance during human-robot physical interaction. A method is proposed that implements virtual constraints in Cartesian admittance control in order to prevent the operator from guiding the manipulator to low-performance configurations. The constraints are forces expressed in the Cartesian frame, which restrict the translation of the end-effector when the operator guides the robot below a certain performance threshold. These forces are calculated online by numerically approximating the gradient of the performance index with respect to the Cartesian frame attached to the end-effector. An experimental evaluation is conducted involving human-robot interaction with a 7-DOF LWR serial manipulator under Cartesian admittance control, using the kinematic manipulability index of the manipulator as the performance measure for singularity avoidance.