Research On Hybrid Optimizing And Verification Of Unmanned Surface Vehicle Path

Nowadays,the research of USV has become a hotspot.In order to improve the level of autonomy of USV,this paper proposes a ship collision risk assessment algorithm and a USV path planning algorithm based on support vector machine,and carries out theoretical analysis and virtual reality simulation to validate these two algorithms.Firstly,this paper elaborates the significance of the research and introduces the research status of collision risk assessment algorithm and path planning.Secondly,it introduces the optimization theory and the related knowledge of SVM,lists some theorems and properties of the theory,and gives the theoretical deduction and proof of the important part.Thirdly,the feasibility of using relaxed variables in SVM alorithm to evaluate collision risk is analyzed.Then the principle of the algorithm is systematically expounded,and the characteristics of the algorithm are analyzed and summarized.Finally,the solution method and formula of the collision risk assessment alorithm are given and simulated in the environment of MATLAB.Then,a path planning algorithm based on extended SVM is presented.The construction idea of the path planning model is explained,and the properties of the path planning model are analyzed and proved.Then the algorithm steps of solving the model are given,and the simulation is carried out.Finally,in the Vega Prime based virtual reality simulation platform for USV,the two algorithms proposed in this paper are verified.On the virtual reality platform,the collision risk assessment algorithm is used to calculate the collision risk between the USV and the surrounding obstacles in real time.In the virtual environment,the path planning algorithm is used to plan the navigation path of the USV.