Online Graph Pruning for Pathfinding On Grid Maps

Daniel Harabor, Alban Grastien

Proceedings of the AAAI Conference on Artificial Intelligence · 2011 · 378 citations · 12 references

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TL;DR

Pathfinding in uniform‑cost grid environments is common in robotics and video games, yet current hierarchical algorithms are fast and memory‑efficient but often produce suboptimal paths. This work introduces a grid‑specific search strategy that is fast, optimal, and requires no memory overhead. The algorithm employs a macro operator that identifies jump points and expands only those nodes, leaving intermediate nodes between jump points unexpanded. Empirical results show that using jump points accelerates A* by at least an order of magnitude and yields significant improvements over the state of the art.

Abstract

Pathfinding in uniform-cost grid environments is a problem commonly found in application areas such as robotics and video games. The state-of-the-art is dominated by hierarchical pathfinding algorithms which are fast and have small memory overheads but usually return suboptimal paths. In this paper we present a novel search strategy, specific to grids, which is fast, optimal and requires no memory overhead. Our algorithm can be described as a macro operator which identifies and selectively expands only certain nodes in a grid map which we call jump points. Intermediate nodes on a path connecting two jump points are never expanded. We prove that this approach always computes optimal solutions and then undertake a thorough empirical analysis, comparing our method with related works from the literature. We find that searching with jump points can speed up A* by an order of magnitude and more and report significant improvement over the current state of the art.

References

12