Real-time optimal path planning for mobile robots based on immune genetic algorithm

Abstract

A novel method of optimal path planning for mobile robots was presented based on the proposed immune genetic algorithm with elitism(IGAE).The steps are as follows.Firstly,the grid theory is utilized to establish the free space model of the mobile robot in a given environment,and a sequence number is used to identify a grid.The sequence numbers are used to code the moving path of mobile robot.Secondly,the rectangular coordinates and the sequence number method are used to produce the initial population of IGAE,that is,the initial chromosomes are generated with a string of sequence numbers.Finally,an insertion operator and a deletion operator are defined to ensure that each obtained path is continuous and collision-free in the evolutionary process of IGAE.The results show that the proposed method is better than the genetic algorithm with elitism in the globally optimal path planning of mobile robots.