Research On Unmanned Surface Vehicle Navigation Control And Swarm Collision Avoidance

The autonomous navigation of unmanned surface vehicles is highly valued in military and civilian areas.In the military field,unmanned boat swarm cooperative control has a wide range of applications in fleet cooperative operations,search and rescue,formation patrol,and so on In civil fields such as marine resource detection and environmental monitoring,the use of multiple unmanned boat swarm systems can increase the scope and efficiency of monitoring tasks.In this paper,the swarm is used as the research object to optimize the stability and accuracy of each member boat forming the swarm.On this basis,further research is made on swarm separation and convergence for swarm collaborative path tracking,obstacle avoidance,and multi-path tracking tasksFirst,a three-degree-of-freedom model of the surface of the unmanned boat is established The control law is designed with the thrust and the nozzle angle as inputs to realize the decoupling control of the speed and heading of the unmanned surface vehicles.Aiming at the problem of the compensation of the sideslip angle during the navigation of the unmanned boat,a neural network-based prediction of the sideslip angle of the LOS path tracking controller was proposed to improve the accuracy of the unmanned boat path tracking.Aiming at the uncertainty of hydrodynamic parameters and nozzle corner failure in unmanned boat movement under complicated conditions,an adaptive reconstruction control law is designed to further improve the stability of unmanned boat path tracking.in this way,The human boat can complete the desired path tracking task in the state of uncertain parametersThen,based on the optimization in both accuracy and stability of the single boat motion control.Aiming at the problem of cooperative navigation of unmanned boat swarms,a virtual structure method is adopted to maintain navigation stability,and the concept of dispersion is proposed to maintain a fixed distance between members of unmanned boat swarms,and the Lyapunov's stability theorem is used to prove the effectiveness of the swarm collaboration method;Aiming at the problem of multi-path swarm path following in the same navigation task,experiments were further designed to realize the separation and convergence of the six-member unmanned boat,and a simulation verification test was carried out.Finally,for the problem of collision alvoidance of internal member boats during the unmanned boat swarm navigation,an improved artificial potential field method was adopted to solve the problem of collision avoidance within the swarm.Aiming at the obstacle avoidance of external obstacles,combining the maritime rules-based collision avoidance behavior method with artificial potential field method,the unmanned boat collision avoidance area is established with the unmanned boat as the center,and different obstacle avoidance strategies are designed in different areas.A swarm control system with an autonomous obstacle avoidance system is established to achieve autonomous obstacle avoidance for unmanned boat swarms during path following tasks.Based on the above,multiple paths and obstacles are designed in a swarm navigation task,and the swarm member boat is separated into two sub-swarm,performing different path following and obstacle avoidance tasks respectively,and then they are merged into the same swarm to continue navigation.This method further improves the mission efficiency and navigation efficiency of the UAV swarmSimulation results show that the accuracy of path following is improved,the overshoot and response time are reduced,thus the stability of navigation is further improved.In the simulation of swarm navigation and obstacle avoidance,when the unmanned boat swarm encounters obstacles,it can flexibly adopt its own best control behavior to avoid obstacles while ensuring safety and accessibility,and able to converge quickly and continue to maintain swarm navigation.