Global Path Planning for Multi-Task Assignment Based on Improved Genetic Algorithm for Multi-USV
In order to complete the assignment of multiple tasks,the shortest total path of unmanned surface vehicle(USV)cluster navigation and the shortest path length gap of each USV are ensured,the genetic algorithm is improved from three aspects of initial population generation,selection and mutation operator.According to the characteristics of obstacles in navigation area,the tangent method is used to optimize the path generated by improved genetic algorithm.In order to verify the effectiveness of the algorithm,a simulation model is built based on MATLAB/Simulink simulation platform,and the multi-task global path planning test is carried out according to the specific navigation environment.The proposed algorithm can realize the global path planning of USV cluster multi-task assignment as the simulation results showed.
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