Research On Fast Route Planning Method Adapted To Directional Endpoint Constraints

With the wide use of route planning in mailitary, aviation and aerospace fields, more and more researchers begin to conduct researches around this area, and a variety of algorithms have been proposed to meet the different constraints of the route planning problem. The traditional path planning algorithms seldom consider the constraints of directional endpoints. In the planning process, once the path reaches the target in any direction, the planning is considered to have been finished. However, In applications, aircraft often departure in a predetermined direction and arrive along a specified direction to escape certain threats and improve the efficiency of penetration. This paper studies on this issue.In this paper, the research status of the path planning field is introduced, and a brief description of three typical planning algorithms is given. Then the basic principles and processes of the A*algorithm is described in detail. This paper also discussed the optimality effect of the heuristic funciton of the A*algorithm. Then, gives descriptions of the role and implementation of two key elements in the algorithm, the Open table and the Close table. Based on these analysis, it is pointed out that there are some limitations in the A*algorithm when it is applied to the route planning problem with the constraints of directional endpoints. The reasonsof the limitation are given and verified through experiments.In the path planning with constraints of directional endpoints, traditional A*algorithm is inefficient due to lack of direction guide. To solve this problem, this paper proposes a dynamic guiding A*algorithm, which introduces dynamic guide points during the searching process of A*algorithm. The dynamic guiding strategies are given, and then a guiding points generation method is proposed. At the same time, this paper designes a new evaluation function, and describes the switch method of the guide points. In the planning process, the dynamic guiding A*algorithm could find the resultant path, which goes from the specific direction of the start point to the fixed direction of the target point, efficiently. Experimental results show that compared with A*algorithm, this new method could generate a satisfactory path as well, while the planning speed is greatly improved. At last, the dynamic guiding A*algorithm is applied to plan path network. The path network could be generated by planning path between two directional endpoints using this method. In the path planning with the constraints of area that must be passed through, this method is also very applicable using the guide information extracted from the area.