Mobile robot path planning based on improved genetic algorithm

Abstract

In view of the disadvantage that the traditional genetic algorithm cannot be planned when it is applied to robot path planning in a special environment, the population initialization method is improved first, and the path planned by the two-way RRT algorithm replaces a part of the initialization population to form an elite population. Then this paper improve the fitness function, add path smoothing coefficients and obstacle coefficients to ensure path quality, and at the same time add elite strategies to speed up the convergence speed; finally, the traditional genetic algorithm, two-way RRT algorithm, and the algorithm of this paper is carried out in the same map environment. The results show that the elite population genetic algorithm proposed in this paper overcomes the shortcomings of traditional genetic algorithms that are difficult to plan paths in special environments, has higher adaptability to the environment, and improves the success rate of path planning.