Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests (2017)
In the multi-robot human guidance problem, a centralized controller makes use of multiple robots to provide navigational assistance to a human in order to reach a goal location. Previous work used Markov Decision Processes (MDPs) to construct a formalization for this problem, and evaluated this framework in an abstract setting only, i.e. without experiments using high-fidelity simulators or real humans. Additionally, it was unable to handle multiple concurrent requests and did not consider buildings with multiple floors. The main contribution of this paper is the introduction of an extended MDP framework for the multi-robot human guidance problem, and its application using a realistic 3D simulation environment and a real multi-robot system. The MDP formulation presented in this paper includes support for planning for multiple guidance requests concurrently as well as requests that require a human to traverse multiple floors. We evaluate this system using real humans controlling simulated avatars, and provide a video demonstration of the system implemented on real robots.
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), São Paulo, Brazil, May 2017.

Piyush Khandelwal Ph.D. Alumni piyushk [at] cs utexas edu
Peter Stone Faculty pstone [at] cs utexas edu