Multi-AUV Collaborative Target Search Based On Ant Colony Algorithm

Autonomous Underwater Vehicle(AUV)is an important part of deep-sea technology and plays a very important role in military and civil affairs.Multi-AUV collaborative target search research can make AUV efficient in the search process.The research of this paper is as follows:Firstly,the environment model,forward looking sonar model,AUV kinematics model and target model are established.Combining the detection range of the sonar and the influence of noise,the way to determine the existence of targets in different areas is established.Based on multiple AUVs participating in the target search,the AUV’s communication adopts global communication,which can strengthen the coordination between AUVs.Provides ideas for follow-up research.Secondly,aiming at the path planning problem of suspected targets in underwater environment,a path planning based on improved ant colony algorithm is proposed.For the path planning based on the ant colony algorithm,which has the disadvantage of poor convergence in dealing with the obstacle avoidance problem of multiple obstacles,an improved method combining maximum probability and roulette is proposed.By introducing random numbers,the convergence of the ant colony algorithm is accelerated;And combined with the advantages of the prior information in the artificial potential field method,the resultant force is introduced into the heuristic information in the early stage of the iteration to speed up the ability of the ant colony algorithm to quickly find the target point in the early stage of the iteration,thereby accelerating the convergence speed of the algorithm.Through simulation comparison,the efficiency of the improved ant colony algorithm is verified.Then,the problem of multi-AUV collaborative target search in unknown underwater environment is analyzed and researched,and a target search algorithm combining ant colony algorithm and probability map is proposed.Through the analysis of AUV synergy,the control method and obstacle avoidance problems between AUVs are solved.Secondly,the ant colony pheromone is introduced into the search process of multiple AUVs,so as to coordinate the target search task between each AUV and solve the coordination problem between AUVs.At the same time,the uncertainty map in the probability map is combined to form the search decision function,which solves the multi-AUV target search decision problem.Through simulation comparison,the feasibility and efficiency of the proposed algorithm are verified.Finally,the multi-AUV cooperative target search in the obstacle environment is discussed.In view of the fact that AUV only relies on the search decision function in the current adjacent grid to make a decision in the target search process,there will be a local optimum problem,an optimization of predictive control is proposed.The function to determine the target search of AUV can greatly optimize the search efficiency of AUV;the collaborative target search of multiple AUVs is real-time,and obstacles will appear.The rolling window method is used to solve the real-time obstacle avoidance problem of AUV,which can effectively avoid obstacles thing.Combined with the path planning of the ant colony algorithm to confirm the authenticity of the target.Through simulation verification,the multi-AUV cooperative target search based on the ant colony algorithm can be realized,and when some AUVs fail,other AUVs can still complete the target search task,which has a certain anti-interference ability.