Unmanned Surface Vehicle Cooperative Task Assignment Based on Genetic Algorithm

Abstract

Task allocation modeling plays an important role in unmanned surface vehicles (USV) collaborative systems. In order to adapt to the complex environment, a cooperative multi-task assignment problem (CMTAP) model suitable for multi-USV, multi-target, and multi-task is designed. The article first clarifies the advantages of collaboration, then based on the traditional genetic algorithm (GA), the crossover and mutation operators are optimized to be more suitable for the current environment. This method utilizes the strong global search ability of GA to optimize the result of cooperative task assignment of USV. Simulation experiments demonstrate the effectiveness of the method.