Despite popular depictions in sci- movies and TV shows, robots remain limited in their ability to autonomously solve complex tasks. Indeed, even the most advanced commercial robots are only now just starting to navigate man-made environments while performing simple pick-and-place operations. In order to enable complex high-level behaviors, such as the abstract reasoning required to maneuver objects in highly constrained environments, we propose to leverage human intelligence and intuition. The challenge here is one of representation and communication. In order to communicate human insights about a problem to a robot, or to communicate a robot's plans and intent to a human, it is necessary to utilize representations of space, tasks, and movements that are mutually intelligible for both human and robot. Our work focuses on the problem of single and multi-robot motion planning with human guidance, where a human assists a team of robots in solving a motion-based task that is beyond the reasoning capabilities of the robot systems. We exploit the ability of Mixed Reality (MR) technology
to communicate spatial concepts between robots and humans, and focus our research efforts on exploring the representations, optimization techniques, and multi-robot task planning necessary to advance the ability of robots to solve complex tasks with human guidance.

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