  Our goal is to enable robots to express their incapability, and to do so in a
way that communicates both what they are trying to accomplish and why they are
unable to accomplish it. We frame this as a trajectory optimization problem:
maximize the similarity between the motion expressing incapability and what
would amount to successful task execution, while obeying the physical limits of
the robot. We introduce and evaluate candidate similarity measures, and show
that one in particular generalizes to a range of tasks, while producing
expressive motions that are tailored to each task. Our user study supports that
our approach automatically generates motions expressing incapability that
communicate both what and why to end-users, and improve their overall
perception of the robot and willingness to collaborate with it in the future.
