Path Planning Method Research Based On Improved Ant Colony Algorithm For UUV

With the increasing attention of marine resources,Unmanned Undersea Vehicle(UUV)is widely used by human beings to complete the marine resources exploration and exploitation.Meanwhile,as a kind of maritime force multiplier,the application of UUV in the fields of military,such as underwater reconnaissance,underwater communication,anti-submarine,mine warefare and information warefare also get unprecedented development.Because the development direction of UUV focuses on the intellectualization and far distance,UUV is gradually realizing intelligent control and autonomous navigation.As the most important function of UUV autonomous system,the UUV path planning level marks the intelligence and autonomy of UUV to a certain extent.Meanwhile,it is also the key to ensuring the safe and reliable work of UUV.The paper concentrate on the application of ant colony algorithm on UUV path planning.By combining the background of UUV application and based on improved ant colony algorithm,respectively,the paper discusses the UUV off-line path planning method,the UUV on-line real-time path planning method and the UUV complete coverage path planning method.Eventually,the improved ant colony algorithm and all of the UUV path planning method developed were tested in simulation experiment.The main contributions of this thesis are summarised as follows:Due to the defects of the existing ant colony algorithm,such as slow solving speed and easy falling into local extremun,this paper improves the existing ant colony algorithm and applies the improved ant colony algorithm to UUV off-line path planning.It is improved by simulation experiments that the improved ant colony algorithm has higer environment adaptability and the higer convergence precision.The UUV on-line real-time path planning method is proposed by combining improved ant colony algorithm with rolling window path planning method to mainly solve the problem of UUV avoiding dynamic odstacles.By introducing the guide point strategy,this paper links global path planning to local path planning,which not only meets the requirements of real –time on-line path planning,but also considers the global optimality target.In order to solve the problem of area coverage search,the paper come up with a complete coverage path planning method to integrate the improved ant colony algorithm into biologically inspires neual network.Simulation experiments in a variety of complex environment show that the presented method has the higher coverage rate and the lower repeat rate,and it could meet the requirement of traversal search for UUV.Based on all of the above ideas and methods demonstrated by lots of simulation experiments,it shows that the presented path planning methods make full use of the advantages of global optimization and strong adaptability.Also,it could solve the problems of three kinds of path planning for UUV.It is highly emphasized that the presented methods have important theoretical significance and application value to meet the requirements of safety and economic navigation for UUV.