Mobile Robot Path Planning based on Improved Genetic Algorithm With A-star Heuristic Method

This paper proposes an improved genetic algorithm to achieve efficient searching capabilities of path planning in complicated maps for mobile robot. The improved genetic algorithm uses the evaluation function of A-Star (A*) algorithm. Firstly, the grid environment model is constructed. The evaluation function of A* algorithm and the bending suppression operator are introduced to improve the heuristic information of the genetic algorithm, which accelerates the convergence speed during the search. Secondly, the insertion operators and deletion operators are introduced into the traditional genetic operators, meanwhile, the consistency of path planning is considered in fitness function, which calculating the fitness values of each path. Output the path with the highest fitness value as the optimal path. The simulation results show that the improved genetic algorithm has less iteration number and can get a better solution than the traditional genetic algorithm.