Research On Path Planning For Recovery Of Underwater Autonomous Vehicle

In recent years,the Autonomous Underwater Vehicle(AUV)stands out among a series of submersible vehicles with its mission autonomy,convenient deployment,and convenient modification,and has become the first choice for completing various underwater tasks.It is necessary for AUV to achieve autonomous navigation and docking in the recovery task.Due to the complex and changeable characteristics of the marine environment and the limitations of the AUV 's own energy resources,designing a return route can simultaneously meet obstacle avoidance requirements and improve AUV endurance is very important.It has great significance to ensure recycling and docking successfully.In order to solve the problems of too simple models in traditional AUV path planning,which leads to poor actual planning ability and insufficient specificity research,which cannot be applied to recycling tasks,this paper has conducted in-depth research.Based on the small AUV and static recovery docking platform developed by the laboratory,this paper analyzes the specific requirements of path planning in different stages of the recovery process,divides the path planning in the recovery process into three sub-problems,and studies them separately.Propose a set of path planning methods for AUV recycling docking.The main research contents are as follows:Firstly,in view of the problem of ocean current interference in global path planning,an energy cost function for navigation under irregular ocean currents based on the AUV energy consumption model is proposed.In order to solve the problem of premature convergence and rough path in the traditional path planning method,a path update mechanism based on Moth Flame Algorithm is proposed.To avoid searching into local optimum,improve the global search ability.Complete global path planning based on known marine environment information.The feasibility of the method is verified by designing simulation experiments.Then,aim at the real-time collision avoidance problem of unknown complex motion obstacle threat.The extended Kalman filter algorithm is used for state estimation and trajectory prediction of obstacle state information obtained by forward-looking sonar sensors.Determine the risk of collision between AUV and obstacles.A compound collision avoidance strategy that adjusts course and speed is used.A planning method based on velocity vector synthesis is proposed to achieve efficient real-time collision avoidance to complete online path planning.The feasibility of the method is verified by designing simulation experiments.Finally,aiming at the problem of constraining the direction of the docking of the interface to the AUV at the end of the recovery task.A guidance path planning method based on improved artificial potential field method is proposed.By setting a virtual spherical repulsive field behind the center of the counter interface and designing a segmentation function of the gravitational field,the AUV approaching the docking platform from any direction can reach the center of the counter interface along a smooth arc path,Increasing the success rate of docking.The feasibility of the method was verified by designing simulation experiments.