Research Of Artificial Intelligence And The Application Of Robot Path Planning

Robot path planning plays a prominent role in the whole robot motion process. The usingefficiency of robots can be greatly improved, and also the robots can be accurately andeffectively applied to the specified and regulated work by a good path planning algorithm.Robot path planning is considered as constrained optimization problem. Optimizationalgorithm can be divided into global path planning and local path planning. A robot can beobtained whole respect guidance by global path planning, and the robot real-time control canbe strengthened and also the path of robot can become smoother by local planning. If combinethe global planning with the local planning, the aim of local planning can be clearer and theblindness of the motion caused by local planning can be avoided.This paper presents a new approach for robot path planning. In order to obtain moreoptimal path, this paper studies path planning algorithm through combining the global pathplanning with local path planning algorithm. A novel method to plan robot’s path is proposed.Firstly, wavelet neural network and genetic algorithm are used to optimize the global paths.Secondly, according to the moving direction of a robot is determined by the resultant force ofattraction and repulsion, the artificial potential field is applied to the local planning, so therobot can avoid obstacles and keep moving direction. Thirdly, genetic algorithm is used tooptimize some parameters of the potential function, and the method of the virtual obstacles isadopted to help the robot can escape local minimum.Based on the given algorithm, two robot path planning simulation platforms of2Dsituation of the discrete and2D continuous situation can be designed through VS2005software and VC++6.0software respectively. The simulation experiments are given undercontinuous situation of barrier, barrier-free and many robots. The simulation analysisdemonstrate that the simulation results based on hybrid intelligence algorithm withcombination the global and local path planning have better results, effectiveness andreasonableness.