Research on the Global Path Planning of Mobile Robot Based on Improved A* Algorithm

Abstract

 Aiming at the problems of many redundant inflection points and low smoothness in the path planning field of the traditional A* algorithm, an improved A* algorithm based on a strong angle change penalty and the smooth path is proposed. Firstly, by introducing the penalty function of angle change cost to optimize the node evaluation function, redundant inflection points in the path can be effectively reduced. Finally, the fourth-order Runge-Kutta algorithm is used to smooth the path, which comprehensively considers the attraction of the original path, the smoothing force of the path movement, and the repulsive force of the obstacle, so as to improve the smoothing quality of the path. With the help of MATLAB, the simulation experiment is carried out, and the effect of path planning is compared and analyzed under the influence of different cost penalty scaling coefficient k, and the optimal k value is determined to be 2. In the experiments of diverse raster map environments, the improved A* algorithm has excellent performance in optimizing the path length and reducing the number of nodes, especially in random and complex environments, which are optimized by 3.68% and 37.50% respectively. The simulation results meet the smooth motion requirements of the actual environment, and the global path planning performance of the A* algorithm has been significantly improved.