Shared Autonomous Interface for Reducing Physical Effort in Robot Teleoperation via Human Motion Mapping

Motion mapping is an intuitive method of teleoperation with a low learning curve. Our previous study investigates the physical fatigue caused by teleoperating a robot to perform general-purpose assistive tasks and this fatigue affects the operator's performance. The results from that study indicate that physical fatigue happens more in the tasks which involve more precise manipulation and steady posture maintenance. In this paper, we investigate how teleoperation assistance in terms of shared autonomy can reduce the physical workload in robot teleoperation via motion mapping. Specifically, we conduct a user study to compare the muscle effort in teleoperating a mobile humanoid robot to (1) reach and grasp an individual object and (2) collect objects in a cluttered workspace with and without an autonomous grasping function that can be triggered manually by the teleoperator. We also compare the participants' task performance, subjective user experience, and change in attitude towards the usage of teleoperation assistance in the future based on their experience using the assistance function. Our results show that: (1) teleoperation assistance like autonomous grasping can effectively reduce the physical effort, task completion time and number of errors; (2) based on their experience performing the tasks with and without assistance, the teleoperators reported that they would prefer to use automated functions for future teleoperation interfaces.