Research On Optimal Path Planning Of Autonomous Ships In Complex Water

Under the situation of globalization of world trade and economic integration,maritime traffic is increasingly busy,and the environment of ships sailing on the sea is more and more complicated.With the rapid development of computer technology and information technology today,in the context of the era of big data,many studies have begun to combine these three technologies into the design of ships to create intelligent ships.Intelligent navigation of intelligent ships is a hot research field of intelligent ships at present,and autonomous navigation is a hot topic in intelligent navigation.Ships will inevitably collide with obstacles in the environment in the process of sailing.One of the purposes of developing intelligent ships is to reduce casualties and economic losses.Therefore,in the study of autonomous navigation of intelligent ships,special attention should be paid to the study of collision avoidance.On this basis,this paper studies the path planning problem of autonomous navigation intelligent ship in complex waters,and carries out simulation experiments to verify the effectiveness of the algorithm.Firstly,the development of intelligent ships in the world and the research status of path planning algorithms are studied,and the constraints that ship path planning will be subjected to are explained,including ship kinematics model,ship safety field,ship safety encounter distance and ship collision avoidance standards.Secondly,the basic principles and processes of three different path planning algorithms,namely Dijkstra algorithm,fast random extended tree algorithm and artificial potential field method,are introduced.The improved weighted artificial potential field method is proposed to solve the defects of traditional artificial potential field method.In addition,Dijkstra algorithm,GBB-RRT algorithm and improved weighted artificial potential field method are respectively used to conduct path planning simulation experiments in the static environment of autonomous ships in Hangzhou Bay,East China Sea,and the results are compared and analyzed.It is concluded that the algorithm proposed in this paper can be better combined with ship path planning.Finally,in the same static water environment,to join the known dynamic obstacles,and its movement as a uniform motion in a straight line,and autonomous navigation ships respectively to encounter,cross,overtaking’ll encounter situation,the application of the proposed algorithm for path planning simulation experiment,get a shortest path without collision,prove algorithm to improve the effectiveness of the easy to fall into local minimum value problem.