Single AGV Path Planning Based on Improved a *Algorithm

The <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{A}^{*}$</tex> algorithm is a common path planning algorithm for AGVs, however, the efficiency of the A* algorithm decreases significantly when the motion environment of AGVs is complex. Aiming at the traditional <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{*}$</tex> algorithm, which has the problems of low efficiency of path search and high number of path transitions, an improved <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A^{*}$</tex> algorithm is proposed. Firstly, a raster - based map model is established, followed by an in - depth analysis of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A^{*}$</tex> algorithm's heuristic function and neighbourhood search strategy. By incorporating dynamic optimization into the heuristic function and optimizing the search neighbourhood from eight to five directions, the algorithm minimizes non - articulated point traversal, thereby boosting search efficiency. Secondly, simulations under a Python environment compare the improved and traditional <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A^{*}$</tex> algorithms using identical raster maps. Results indicate that the enhanced algorithm reduces search time and path expansion nodes by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{7 2. 3 \%}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6 5. 9 \%}$</tex> on average, respectively, significantly improving overall efficiency.