Application On Research On Intelligent Car Path Planning Based On Graphplan

Intelligent planning is a significant branch developed from artificial intelligence. It involves such perspectives as knowledge expression and representation, reasoning, nonmonotonicity, situational calculus,human-computer interaction,knowledge discovery and so on.Therefore,not only does the development of intelligent planning play an important role in the development history of artificial intelligence, but also in other related scientific fields.Since the concept of intelligent planning was first presented in 1950 s, scholars of various fields have put forward different planning methods, among which is the Graphplan algorithm proposed by Blum and Furst. Based on planning graph,this approach has aroused heated concern. In Graphplan, the programming problem produced by the STRIPS rules will be translated into the forms of graphs, the solution of which will be later extracted with the path research approach. In this way, this approach excels in that it takes the advantages of parallel execution and thus, increases the efficiency of solving problems.This paper takes an intelligent car as the research subject, introducing the background information, as well as the significance of the intelligent car in tracing problems. Through the analysis of the deficiency of the intelligent car Path Planning, this paper tries to focus on solving the tracing problems with the intelligent planning method. The intelligent car in the paper is designed by using microcontroller STC89C52 as a controlling core, with the aim to implement the tracing system of intelligent cars. Moreover, the implementation and designing scheme of the system are discussed in the paper in detail. In this way, the intelligent car is able to work autonomously to reach fire sources and put the fires out without any external control. The researcher in this paper puts forward a tracing scheme based on graphplan by referring to a large amount of references and combining the ideas of intelligent planning. A tracing algorithm of graphplan is added in the tracing scheme, with whose guidance, the car is able to avoid obstacles autonomously in motion and move in an optimal path. Compared with other conventional tracing schemes, the method involves fewer less comparisons and with this method, serial or parallel solution can be obtained, improving the tracing efficiency to some extent.