Research On Path Planning For Mobile Robot Based On The Genetic Algorithm

Intelligent mobile robot is the vehicle that can finish the running task without artificial intervention. Path planning is a kernel problem of robot technology area.The main task of path planning is figuring out a collide-free path at least cost from the known start position to known goal position in the robot environment. Genetic algorithm is a random,iterative and evoloutional process based on natural selection and population genetics mechanism.The paper firstly studies the elementary theory of genetic algorithm and presents the path planning method of the robot based on the genetic algorithm which combines the feature of the path planning problem. Secondly,we present the navigation and path planning technology of the mobile robot,particularly the genetic operator.Based on the traditional genetic operator,smooth,interposition and deletion operators are joined in.At the same time,self adaptation of aberration rate and crossing-over rate is also used which is to make the algorithm more perfect.Finally, the choice of key parameter is determined after analyzing simulation experiment result in three static environment, and the dynamic path planning is simulated.Comparing with the other methods, it is found that in the same environment the search time of genetic algorithm can save 5 percent at least compared to ant colony algorithm,and this method is better than Dijkstra algorithm in space complexity, in other words, genetic algorithm is smaller than the Dijstra algorithm in memory space.It's proved that the application of the genetic algorithm can solve the path planning problem of mobile robot in the dynamic or static environment.