Multi-Agent Planning for Persistent Missions with Automated Battery Management

This paper introduces and demonstrates a full hardware testbed for research in long-duration missions for multiple, autonomous agents. Speci cally, we describe an automated battery management platform designed to service multiple quadrotor agents in the MIT RAVEN and Boeing VSTL ight environments. The changing/charging station allows the quadrotor’s spent battery to be quickly swapped for a fresh one without requiring it to power down or wait for recharge a signi cant bene t in persistent and/or time-critical missions. We focus on a multi-agent persistent search and track scenario and construct both centralized and decentralized MDP-based mission planners. We further show that for the three agent case, decentralized planners (one for each agent) o er a 99% reduction in computation time and only a relatively small (10%) degradation in overall mission performance when compared to the centralized approach over a long-term simulated mission.