Abstract

This article discusses widely used algorithms for finding optimal paths. Currently, there is a fairly wide list of algorithms for the problem of finding the shortest path, and is actively used in mobile robotics to find the optimal route. The article offers a two-level system that performs traffic planning. Comparative analysis of various search methods was carried out: their length, complexity, and a number of turning points. The purpose of the article is to study and compare algorithms from the field of artificial intelligence for finding the shortest path in a maze and a hexagonal grid. Algorithms under study: A* (star), Dijkstra algorithm, BFS, DFS, and Greedy algorithm. Algorithms are compared based on two criteria: the length of the found path and the time it takes to find the path. The results, presented analytically and graphically, show the application of five algorithms for mazes with different size and number of obstacles.

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