  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 (Reachability-Expressive Motion Planning), which jointly
optimizes the physical cost and the expressiveness of robot motion to reveal
the robot's motion capability 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.
