Optimizing a search strategy for multiple mobile agents

摘要

ABSTRACT In this paper, we propose a rule-based search method for multiple mobile distributed agents to cooperativelysearch an area for mobile target detection. The collective goals of the agents are (1) to maximize the coverage ofa search area without explicit coordination among the members of the group, (2) to achieve sucient minimumcoverage of a search area in as little time as possible, and (3) to decrease the predictability of the search pattern ofeach agent. We assume that the search space contains multiple mobile targets and each agent is equipped with anon-gimbaled visual sensor and a range-limited radio frequency sensor. We envision the proposed search methodto be applicable to cooperative mobile robots, Unmanned Aerial Vehicles (UAVs), and Unmanned UnderwaterVehicles (UUVs). The search rules used by each agent characterize a decentralized search algorithm wherethe mobility decision of an agent at each time increment is independently made as a function of the directionof the previous motion of the agent, the known locations of other agents, the distance of the agent from theboundaries of the search area, and the agents knowledge of the area already covered by the group. Weights andparameters of the proposed decentralized search algorithm are tuned to particular scenarios and goals using agenetic algorithm. We demonstrate the eectiveness of the proposed search method in multiple scenarios withvarying numbers of agents. Furthermore, we use the results of the tuning processes for dierent scenarios todraw conclusions on the role each weight and parameter plays during the execution of a mission.Keywords: distributed control, cooperative search, unmanned aerial vehicles, search, genetic algorithms