Research On Key Technologies For Group Obstacle Avoidance In Swarm Formation Of Unmanned Surface Vehicles

The ocean has abundant resources,and countries around the world attach great importance to their rational use and development,which requires a large number of vessels to operate at sea.However,the marine environment is complex and ever-changing,and traditional manned vessels have low safety and are difficult to perform some dangerous tasks.As an important equipment for modern marine work,unmanned surface vessels have great potential in marine exploration,transportation,and military fields.Traditional single-boat path planning can only complete simple tasks,while a formation of multiple unmanned vessels can greatly reduce the burden on operators and have stronger fault tolerance and efficiency in task execution,making it a focus of current unmanned vessel research.This article explores the research in the direction of unmanned vessel formation models,unmanned vessel path planning,and unmanned vessel formation obstacle avoidance.(1)To address the formation control problem in unmanned vessel swarms,this study proposes a navigation virtual structure method,which combines the advantages of the leader-follower method and the virtual structure method to achieve stable control of the formation.First,the six-degree-of-freedom kinematic model of the unmanned vessel is analyzed and simplified to establish the motion equation.Then,with the leading vessel as the leader,the control problem of the unmanned vessel swarm is transformed into the path tracking error problem of the following ship to the virtual structure,and a motion controller and power controller for the unmanned vessel are designed,combining the backstepping method and the sliding mode control structure,with Lyapunov theory and Barbalat’s lemma proving the stability of the system.Finally,simulation experiments are conducted,and the simulation results show that the formation controller is stable and reliable,and the formation effect is satisfactory.(2)To address the obstacle avoidance problem in global path planning for unmanned vessels,an improved A* obstacle avoidance algorithm is proposed,which combines a safety distance evaluation function and a pruning strategy to ensure the safety of unmanned vessel navigation.First,an evaluation function for safety distance is added to the A* algorithm to increase the safety of the planned path,ensuring that unmanned vessels have sufficient space to avoid in emergencies and achieve safe obstacle avoidance.Then,a pruning strategy is used to eliminate redundant points in the path,improve the compactness of the path,optimize the turning points of the path,reduce the degree of path curvature,shorten the distance of the planned path,and improve the driving efficiency.Finally,simulation experiments are conducted and compared with traditional obstacle avoidance algorithms.The simulation results show that the improved obstacle avoidance algorithm with safety distance has higher safety and fewer turning points in the path.(3)To address the dynamic obstacle avoidance problem in unmanned vessel formation path planning,a global induction and velocity obstacle measurement method is proposed to improve the efficiency of unmanned vessel navigation.First,the safe and reliable route planned by the improved A* algorithm with safety distance proposed in the fourth chapter is taken as the preset global route,and the collision domain is obtained by preprocessing according to the speed information of dynamic obstacles.Then,the improved velocity obstacle method is integrated with global path information to calculate the best offset angle for the unmanned vessel to perform local path planning.The leading vessel moves forward according to the local route,while the other vessels maintain their formation according to the formation model proposed in the third chapter.Finally,simulation experiments are conducted in multi-obstacle scenes,and the simulation results show that the global induction and velocity obstacle measurement method can fully utilize the information of global path planning,while considering the safety distance between unmanned vessels and obstacles.The planned path is efficient and safe.