Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaboration
This addresses the problem of establishing common ground for non-expert users in human-robot collaboration, though it is incremental as it builds on existing calibration and motion planning approaches.
The paper tackled the problem of aligning human perception of a robot's reachable workspace with its actual capability to improve collaboration. The result showed that a short calibration using their REMP method effectively bridged this gap and led to more efficient joint tasks.
Aligning humans' assessment of what a robot can do with its true capability is crucial for establishing a common ground between human and robot partners when they collaborate on a joint task. In this work, we propose an approach to calibrate humans' estimate of a robot's reachable workspace through a small number of demonstrations before collaboration. We develop a novel motion planning method, REMP, which jointly optimizes the physical cost and the expressiveness of robot motion to reveal the robot's reachability to a human observer. Our experiments with human participants demonstrate that a short calibration using REMP can effectively bridge the gap between what a non-expert user thinks a robot can reach and the ground truth. We show that this calibration procedure not only results in better user perception, but also promotes more efficient human-robot collaborations in a subsequent joint task.