An improved IGA based path planning of mobile robot in dynamic environment

Abstract

Aimed at the path planning problem of mobile robot in dynamic environment, an improved IGA named A-IGAE is proposed. In this paper, path planning of mobile robot in uncertain environment is designed, and grid method is utilized to make environment modeling. Firstly, adaptive crossover and mutation probability strategy is introduced in order to solve the main conflict of the convergence speed with the global astringency. Secondly, elitist reservation strategy is brought to maintain the good diversity of a population and improve quality of the population. Thirdly, improved roulette wheel selection strategy is used to select and suppress antibodies. Finally, the deletion operation and insertion operation are defined to ensure that each obtained path is continuous and collision-free in the evolutionary process of A-IGAE. The validity of the proposed algorithm is verified by the results of simulations.