An improved A* algorithm is proposed to address the issues of low search efficiency,path diagonally crossing obstacle vertices,and excessive turns in mobile robot path planning. Firstly,a strategy is introduced to avoid diagonally crossing obstacle vertices during the neighborhood expansion in the A* algorithm. Secondly,an exponential weight is applied to the evaluation function based on obstacle factors to reduce unnecessary search and improve the efficiency and adaptability of the A* algorithm,favoring paths with fewer obstacles. Finally,a three-phase optimization strategy is employed,considering the obstacle safety distance,to minimize redundant nodes and turns in the path. MATLAB simulations are conducted in grid maps of sizes 20×20 m,40×40 m,and 60×60 m. The results demonstrate that the improved A* algorithm significantly reduces search time by 70.12％,84.31％,and 91.44％,respectively,and reduces the number of expanded nodes by 53.77％,71.20％,and 74.30％,respectively. Moreover,the accumulated turning angles in the path are reduced by 70.48％,76.31％,and 82.18％,respectively. The improved A* algorithm effectively enhances the efficiency of mobile robot path planning,resulting in smoother and safer paths,especially in complex environments.
万方数据
