Abstract: In application scenarios of the A* algorithm, when there are few or no obstacles around the parent node, path searching should theoretically become relatively straightforward. However, the A* algorithm still adheres to established rules for node expansion, often leading to unnecessary redundancy in expanding child nodes. To address this issue, this paper proposes an application scenario driven A* algorithm (ASD-A*), which dynamically selects different node expansion step sizes by detecting the number of obstacles near the current node, thereby improving node expansion efficiency. Meanwhile, in response to the flexibly varying node expansion strategy proposed in this paper, a method for parallel implementation of the ASD-A algorithm on the dynamically self-reconfigurable array is introduced to further accelerate the path planning process. Simulation results demonstrate that the ASD-A* algorithm reduces the average time required for path planning by 17.7% compared to the original algorithm across scenarios with varying numbers of obstacles.

Key words: dynamic self-reconfigurabla, array processor, A* algorithm, parallelization