The Research Of Intelligent Car Path Planning Based On The Genetic Algorithm

Intelligent car is a kind of robot,which palys an the an irreplaceable role in the human society. Mobile robot has became research hot subject of people recently. Path planning and obstacle-avoidance is both important topic among the robot research. It mainly functions is how to make the robot get a minimum cost path in an obstacles environment. Genetic algorithm is a very effective method of robot path planning , which is based on genetics and natural evolution, an random iterative evolution process.This paper first introduced the car environment perceptual system, it is the car 's eye,which proposed some strategies to information processing. Then the paper doing some research on path planning using our improved genetic algorithm. In addition to basic genetic operator, according to the particularity of the path planning, joined the optimization operator, delete operator and insert operator. For crossover probability and mutation probability, this paper presents a fuzzy control method which make real-time setting. Thus this method greatly optimization of genetic algorithm. Make the improved algorithm more stable. Based on the static environment, puts forward an path planning problem solutions in the moving obstacles of dynamic environment。Core ideology is the use of static dynamic viewpoint to solve the problem.Finally, This paper using the matlab to do the simulation of the algorithm. Doing the simulation in three different obstacles of the environment。Our improved genetic algorithm are found an approximate optimal path in these three different environments. Finally the path planning in dynamic environment is simulated,Results show that, the improved genetic algorithm in this paper can do an very good solution of the static and dynamic environment of mobile robot path planning problem。...