基于人工势场法的迷宫路径搜索算法设计

Maze solving algorithm based on artificial potential field method

在针对迷宫的众多搜索算法中,大部分算法都不能保证在任意迷宫中有很好地表现,为了寻找一种适应性强且比较高效的搜索算法,本文提出了一种基于人工势场法的迷宫路径搜索算法.该算法增强了电脑鼠对迷宫路径未知部分的预测能力和岔口选择的决策能力,同时能够实现最优路径的选择.通过数学建模和定性分析,并运用电脑鼠实际测试,证明了此算法的可行性和可靠性.

In many search algorithms for the maze,most algorithms are not guaranteed to have the very good performance in any of the labyrinth,in order to find a good adaptability and more efficient search algorithm,this paper puts forward a kind of depth-first search（ DFS） algorithm based on the artificial potential field method. This algorithm strengthens the ability of unknown things prediction and making decision for multiply roads. In the meanwhile,this algorithm can help the mouse make the optimal path selection. It has also been proved that this algorithm can be operated accurately with the mathematical modeling and the mouse test in reality.