Multiple USV cooperative algorithm method for hunting intelligent escaped targets

Abstract

ObjectivesA multiple unmanned surface vehicle (USV) cooperative hunting algorithm based on the double layer switching strategy is proposed to cope with the difficulties of USVs in hunting intelligent escaped targets. MethodsSpecifically, the first hunting strategy adopts the improved potential point method. The Hungarian algorithm is employed in order to dynamically allocate potential points for USVs, and the optimization goal is applied to minimize the total linear distance between USVs and potential points. In this process, the artificial potential field method is used to achieve cooperative collision avoidance. The second hunting strategy takes advantage of the nature of the Apollonius circle to tighten the surrounding area, i.e. two USVs go to the target point of the escaped target to intercept it, while the remaining USVs maintain the same direction as the escaped target. Moreover, in order to deal with the different escape strategies of targets, the first and second layers of hunting strategy can be transformed into each other.ResultsNumerical simulation shows that the proposed algorithm can reduce the hunting time to less than or equal to that of the sequential distribution potential point algorithm and polar angle distribution potential point algorithm.ConclusionsThe results of this study prove the effectiveness and progressiveness of the proposed algorithm.

Keywords

• unmanned surface vehicle (usv)
• cooperative hunting algorithm
• potential point method
• hungarian algorithm
• apollonius circle