Experimental assessment of human-robot teaming for multi-step remote manipulation with expert operators

Abstract

Remote robot manipulation with human control enables applications where safety and environmental constraints are adverse to humans (e.g. underwater, space robotics and disaster response) or the complexity of the task demands human-level cognition and dexterity (e.g. robotic surgery and manufacturing). These systems typically use direct teleoperation at the motion level, and are usually limited to low-DOF arms and 2D perception. Improving dexterity and situational awareness demands new interaction and planning workflows. We explore the use of human-robot teaming through teleautonomy with assisted planning for remote control of a dual-arm dexterous robot for multi-step manipulation, and conduct a within-subjects experimental assessment (n=12 expert users) to compare it with direct teleoperation with an imitation controller with 2D and 3D perception, as well as teleoperation through a teleautonomy interface. The proposed assisted planning approach achieves task times comparable with direct teleoperation while improving other objective and subjective metrics, including re-grasps, collisions, and TLX workload. Assisted planning in the teleautonomy interface achieves faster task execution, and removes a significant interaction with the operator's expertise level, resulting in a performance equalizer across users. Our study protocol, metrics and models for statistical analysis might also serve as a general benchmarking framework in teleoperation domains.