Obstacles Avoidance Path Planning And Control System Of Underactuated Surface Vehicles

At present,as one of the important embodiments of national marine strength,underactuated surface vehicle is gradually becoming a research hotspot of military ’industry and scientific research institutions in various countries.The premise of underactuated surface vehicle to complete all tasks in unknown sea area is to have accurate obstacle avoidance system and tracking control system.In this paper,a scan sonar based hybrid fuzzy artificial potential field obstacle avoidance algorithm and a finite time disturbance based observer motion controller are proposed.The obstacle avoidance path planning and control of the underactuated surface vehicle obstacle avoidance are realized when the distribution of obstacles is unknown and the disturbance of wind,wave and current exists.The traditional artificial potential field method(TAPF)has its outstanding advantages of small calculation and good real-time performance.However,when the USV needs to carry out its mission in the area with complex sea conditions,TAPF often fails to avoid obstacles due to its two problems of goal nonreachable and local minimum.In this paper,an mechanical scanning sonar based improved artificial potential analysis obstacle avoidance method(MSSIAPF-OAM)is proposed.Avoiding the traditional way of planning obstacle avoidance path by using the resultant force,this method calculates the sum potential field of multiple estimation points in front of the USV.Then,the direction of the estimation point with the minimum sum potential field is taken as the desired heading angle of the next motion of the unmanned vehicle,and the feasible obstacle avoidance path is finally determined.The simulation experiments in a variety of complex sea areas show that,compared with TAPF,the unmanned boat based on MSSIAPF-OAM strategy can not only successfully avoid obstacles,but also has a smoother obstacle avoidance path,and its bow angle change amplitude and oscillation times are lower,too.In order to meet the higher requirements for obstacle avoidance performance of Underactuated Surface Vehicles under some working conditions,this paper proposes a scanning sonar based hybrid fuzzy artificial potential field obstacle avoidance method(SSHFIAPF-OAM),which uses the value of the attraction and repulsion potential field to calculate the ratio of them,and uses it as an input of two-dimensional fuzzy controller,so as to more effectively reflect the influence of target points and obstacles.The comparative simulation experiments in complex multi obstacle sea area show that SSHFIAPF-OAM can be used to plan a smoother obstacle avoidance path,and the algorithm can effectively smooth the overall trend of heading angle,reduce the difficulty of follow-up heading angle tracking control,and make the unmanned boat have higher real-time obstacle avoidance performance.Finally,in order to realize the autonomous navigation function from the starting point to the target point in the unknown sea area with multiple obstacles,and considering the various external disturbances in the actual marine environment,this paper designs the motion controller of the underactuated unmmaned vehicle based on the mathematical model of the underactuated USV,which combines the finite time disturbance observer and the robust tracking controller,and combined it with the above-mentioned obstacle avoidance algorithm to form a complete obstacle avoidance path planning and control system of underactuated unmanned boat.From the comprehensive simulation experiment of the total system,it can be seen that in the unknown sea area with complex obstacles,wind,wave,current and other external disturbances,the unmanned boat can complete reliable and efficient dynamic obstacle avoidance,and sail to the target point under the guidance of the planned obstacle avoidance heading angle.The effectiveness and superiority of the system are verified.