Two-Oracle Path Planning Consolidated by Heuristic-Rich Information

Xi Chen, Yue Zhang, Zhang Yonggang

Keywords: intelligent planning, path planning, topping, compressed path database, proximity wildcards

Abstract: Grid-based path planning is a classic problem in AI, widely applied in robotics, computer games, and scheduling. Two oracle path planning (Topping) is a state-of-the-art fast path-finding method for grid maps. Topping iteratively utilizes SRC and JPS oracles to determine the first moves and number of steps, respectively. This enables faster search than SRC, yet incurs high storage and search costs due to inadequate compression. In this paper, we aim to leverage heuristic information as much as possible to enhance the compression performance of Topping and to further improve the search efficiency (i.e., the first-move decision cost). Ultimately, this also improves Topping’s overall search performance. Experiments on five benchmarks (478 maps in total) show that our methods can reduce the first-move decision cost by an average of about 60% (maximum 71%) and achieve a maximum speedup of 48% in runtime. Remarkably, they also have gains in compression performance and reduce storage costs.

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Submission Number: 43