A cooperative search framework for distributed agents

This paper presents an approach for cooperative search of a team of distributed agents. We consider two or more agents, or vehicles, moving in a geographic environment, searching for targets of interest and avoiding obstacles or threats. The moving agents are equipped with sensors to view a limited region of the environment they are visiting, and are able to communicate with one another to enable cooperation. The agents are assumed to have some "physical" limitations including possibly maneuverability limitations, fuel/time constraints and sensor range and accuracy. The developed cooperative search framework is based on two inter-dependent tasks: (1) online learning of the environment and storing of the information in the form of a "search map"; and (2) utilization of the search map and other information to compute online a guidance trajectory for the agent to follow. The distributed learning and planning approach for cooperative search is illustrated by computer simulations.