Research On Wolf Pack Algorithm For Unmanned Surface Vessel Planning And Searching

Unmanned surface vessel(USV)has many advantages such as flexibility,modularity and intelligence,and it can perform missions in complex marine environment.The optimization method of planning and search for USV is studied when USV’s position is known or unknown.The main contents are as follows:Firstly,divided the environment of the fault USV into two mission situations.Introduced the wolf pack algorithm according to characteristics of the task,and establish the OODA task decision model.Then,when the position of the target USV is known,the target function is designed,and the target function is optimized by the wolf pack algorithm.in view of the shortcomings of traditional wolf pack algorithm is easy to fall into local optimum,an USV path planning method based on improved wolf pack algorithm is proposed.In order to enhance the local search ability of scout wolf,the scout wolf wandering behavior is improved to scout wolf parallel wandering so that scout wolf can search for each point twice,and in order to improve the search efficiency of the local optimal solution,the fierce wolf intelligent attack behavior is established,and the fierce wolf adjusts the speed according to its own position.According to the improved wolf pack algorithm,the USV path planning process is designed.Finally,aiming at the problem of low efficiency of multi-USVs target search in unknown environment,a multi-USVs target search method based on wolf pack search algorithm is proposed.The fitness function is designed by using artificial potential field method.Introducing wolf pack algorithm to continuously search the next optimal moving target point for multi-USVs.In order to improve efficiency of individual wolf when no better fitness value position is found,the current optimal position of the wolf pack is added to the predatory behavior rules.In order to improve convergence accuracy of the algorithm,avoid the rules of natural enemies and join the center of the wolf pack.Combining with the nonlinear simplex method,an optimization flow of fitness function based on improved wolf search pack algorithm is designed.Establish update rules for USV moving points and moving point sets and design the target search process for multi-USVs.Simulation results show that the improved wolf pack algorithm is more efficient in USV path planning and target search.