Abstract
Pathfinding is the problem of finding the shortest path between a pair of nodes in a graph. In the context of uniform-cost undirected grid maps, heuristic search algorithms, such as A ★ and weighted A ★ ( W A ★ ), have been dominantly used for pathfinding. However, the lack of knowledge about obstacle shapes in a gird map often leads heuristic search algorithms to unnecessarily explore areas where a viable path is not available. We refer to such areas in a grid map as blocked areas (BAs). This paper introduces a preprocessing algorithm that analyzes the geometry of obstacles in a grid map and stores knowledge about blocked areas in a memory-efficient balanced binary search tree data structure. During actual pathfinding, a search algorithm accesses the binary search tree to identify blocked areas in a grid map and therefore avoid exploring them. As a result, the search time is significantly reduced. The scope of the paper covers maps in which obstacles are represented as horizontal and vertical line-segments. The impact of using the blocked area knowledge during pathfinding in A ★ and W A ★ is evaluated using publicly available benchmark set, consisting of sixty grid maps of mazes and rooms. In mazes, the search time for both A ★ and W A ★ is reduced by 28 % , on average. In rooms, the search time for both A ★ and W A ★ is reduced by 30 % , on average. This is achieved while preserving the search optimality of A ★ and the search sub-optimality of W A ★ .
Highlights
Grid-based pathfinding has been the subject of considerable interest in a number of fields such as video games and robotics navigation
All four search algorithms: A⋆, WA⋆, A⋆ + blocked areas (BAs) and WA⋆ + BA are implemented and compiled using Java SE 8 and all experiments were executed on a Red Hat Enterprise Linux 6 machine with a 2.2 GHz Intel Xeon-E5 processor and a GB DDR3 memory with a speed of 1333 MHz
This paper introduced the concept of blocked areas, which are sub-regions in grid maps where there is no viable path due to obstacles
Summary
Grid-based pathfinding has been the subject of considerable interest in a number of fields such as video games and robotics navigation. A⋆ [1] is a simple, best-first search algorithm that relies on a heuristic function to guide the search towards finding the optimal path between a source node and a goal node in a grid map. Both algorithms use the octile-distance heuristic, which is a commonly-used admissible heuristic function that allows both straight and diagonal movements.
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