Intelligent Mobile Robot Global Path Planning And Simulation

Intelligent mobile robot is an important branch of robot, due to its' great application potential, current research and development of intelligent mobile robot have attracted the attention of a lot of researchers. The problem of global path planning is a very important part of the study of intelligent mobile robot.At the beginning of this thesis the theory and method of global path planning is introduced. This paper summarizes the basic notion, classification, evaluation criterion of the algorithm, etc. The common methods on modeling of environment and searching strategy are reviewed.Then, Probabilistic Cell Decomposition thoroughly explored .The algorithm consists of Cell Shape, Graph Search, Local Path Planning, Cell Splitting, Probabilistic Sampling. Improved Probabilistic Cell Decomposition has been proposed based the algorithm. Compared traditional method, the new algorithm can save more computational time, and the new algorithm can find most optimal path if computational resource is enough.How to enhance development efficiency is a problem for every developer because its development is very complex. The object oriented architecture of path planning help to implement the algorithm of path planning.Last, a simulation system is also developed to run the algorithm. The simulation shows that the algorithm is feasible and efficient.