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The evaluation of heuristic search algorithms highlighted their diverse performances in pathfinding tasks, with D* Lite excelling in obstacle-dense grids and ARA* showcasing efficiency in larger grid sizes. The study introduced a selection algorithm for optimizing pathfinding based on priorities. Future work aims to expand evaluations to dynamic environments and explore various scenario configurations, refining algorithm selection for enhanced pathfinding efficiency.