Path planning of mobile robot based on improving genetic algorithm

In order to solve the prematurity and lower convergence speed in traditional genetic algorithm for robotic path planning, an improved genetic algorithm designed for robotic path planning is proposed. In this algorithm, grids are used to divide the workspace of a robot. with the serial number being adopted to identify the grids. In addition, the genetic operators which correspond to the coding scheme are introduced, and a novel fast random search method based upon probability is proposed to initialize the population in the question. Moreover, differing from the standard GA, a new delete operator is superadded. and elitist strategy is carried out, all these result in the path planning for mobile robots. The simulation results demonstrate that the proposed approach leads to converge at the global optimal value with high rapid. which presents the adaptive performance for the changes of the working environments.