Research On Multi-AUVs Target Search And Hunting Method In Unknown Environment

In recent years,human research and development of the ocean has become increasingly fierce.Target search and hunting for unknown underwater environments has been a hot topic of research.Autonomous Underwater Vehicle(AUV)is a technical means to solve current problems as a flexible and portable underwater device.In this paper,the following research contents includes target search and round-up in unknown environments:Firstly,the collaborative search and hunting task of multi-AUV in the underwater environment is analyzed,and a solution for target search and hunting is proposed.At the same time,a simulation environment model,a forward-looking sonar model,an AUV motion model,and a target motion model are established for the elements needed to perform a task in an unknown environment.Then the influence of underwater communication constraints on multi-AUV cooperative tasks is analyzed.Finally,the specific communication content between AUV systems is introduced.Secondly,the AUV obstacle avoidance problem in unknown environment is analyzed,and a Predictive Guidance Obstacle Avoidance(PGOA)algorithm is proposed in an unknown environment.The algorithm combines the predictive control with the guidance algorithm,and uses the contour convex algorithm and Bezier interpolation to simplify the boundary of the obstacle data collected by the sonar.By combining the obstacle avoidance weight function,the predictive control secondary optimization function is obtained.The AUV predicts the obstacle avoidance track point and combines the guiding method to achieve the purpose of obstacle avoidance.Then,for the target search problem in unknown environment,a distributed dynamic predictive control(DDPC)multi-AUV collaborative target search algorithm is proposed.The search method can control multi-AUVs to perform the target search task by updating the state information of the task environment region and the state of the multi-AUV fed back by the system through the dynamic prediction and the online optimization decision,thereby solving the problem of Multiple AUVs target search in the unknown environment.At the same time,compared with the search results of random method and scan line method in the simulation experiment,it is verified that the proposed algorithm has better target search effect in complex environment,and it is an effective multi-AUVs collaborative target search algorithm.Finally,a dynamic distributed hunting method is proposed for the dynamic target hunting problem,so that the AUV can organize a triangular hunting formation to achieve the goal ofmoving target hunting destruction more quickly.This hunting method solves the problem of rational allocation of hunting potential points in the hunting process.The effectiveness of this method is proved by analyzing the moving target hunting results,the change of the multi-AUV collaborative task area allocation and the search results of static and dynamic targets in simulation case.