Legible Robot Motion Planning

The goal of this thesis is to enable robots to produce motion that is suitable for human-robot collaboration and co-existence. Most mo-tion in robotics is purely functional: industrial robots move to package parts, vacuuming robots move to suck dust, and personal robots move to clean up a dirty table. This type of motion is ideal when the robot is performing a task in isolation. Collaboration, however, does not happen in isolation. In collaboration, the robot’s motion has an observer, watching and interpreting the motion. In this work, we move beyond functional motion, and introduce the notion of an observer into motion planning, so that robots can gen-erate motion that is mindful of how it will be interpreted by a human collaborator. We formalize predictability and legibility as properties of motion that naturally arise from the inferences that the observer makes, drawing on action interpretation theory in psychology. Pre