Pathfinding with Lazy Successor Generation

TL;DR

This paper introduces LaCAS*, a novel pathfinding algorithm that incrementally generates successors to efficiently solve large-scale problems with implicit connectivity, maintaining completeness and convergence to optimal solutions.

Contribution

The paper proposes LaCAS*, a new lazy successor generation algorithm for pathfinding with implicit graphs, improving efficiency while ensuring completeness and optimality.

Findings

LaCAS* solves complex pathfinding instances faster than traditional methods.

The algorithm is complete and converges to the optimal solution.

Extensive evaluations demonstrate LaCAS* effectiveness in large-scale problems.

Abstract

We study a pathfinding problem where only locations (i.e., vertices) are given, and edges are implicitly defined by an oracle answering the connectivity of two locations. Despite its simple structure, this problem becomes non-trivial with a massive number of locations, due to posing a huge branching factor for search algorithms. Limiting the number of successors, such as with nearest neighbors, can reduce search efforts but compromises completeness. Instead, we propose a novel LaCAS* algorithm, which does not generate successors all at once but gradually generates successors as the search progresses. This scheme is implemented with k-nearest neighbors search on a k-d tree. LaCAS* is a complete and anytime algorithm that eventually converges to the optima. Extensive evaluations demonstrate the efficacy of LaCAS*, e.g., solving complex pathfinding instances quickly, where conventional methods falter.