Effect of virtual fixture compliance on human-machine cooperative manipulation

Abstract

In this paper, we present experiments to determine the effect of different virtual fixture compliance levels in a human-machine cooperative manipulation system. Subjects used the JHU Steady Hand Robot with vision-based virtual fixtures to perform three common tasks: curve following, off-path targeting, and object avoidance. The virtual fixtures provided different levels of guidance to the operator, ranging from no guidance to complete guidance. User performance was evaluated based on the error and time for task execution. We developed an algorithm to determine the appropriate compliance level based on the nature of the task. Task parameters considered were time vs. accuracy and user constraint vs. freedom.