Abstract

Regarding global path planning for search and rescue robots, the traditional method of A* algorithm is slow and has many turning points along the intended route, which hinders its searching speed. A new and enhanced A* algorithm is presented in this paper, incorporating the Floyd-trajectory optimization algorithm. The search directions of the traditional A* algorithm were refined from eight to five. Next, we improved the cost estimation function by introducing a weight value to balance the estimated heuristic function value with the actual cost value, thereby enhancing the algorithm’s search efficiency. Finally, we applied the Floyd path optimization algorithm to eliminate redundant nodes from the route. The use of both the Floyd and A* algorithms in combination has been proven through simulations and experiments to improve search results by 40% compared to solely using the A* algorithm. This integration effectively reduces the search scope, diminishes the number of turning points by 63.8%, improves path smoothness, and effectively shortens the planned path length.

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