We consider optimal and anytime algorithms for the Euclidean Shortest Path Problem
(ESPP) in two dimensions. Our approach leverages ideas from two recent works: Polyanya …

We consider optimal and suboptimal algorithms for the Euclidean Shortest Path Problem
(ESPP) in two dimensions. For optimal path planning, Our approach leverages ideas from …

We consider the online version of Euclidean Shortest Path (ESP): a problem that asks for
distance minimal trajectories between traversable pairs of points in the plane. The problem …

Abstract The Euclidean Shortest Path Problem (ESPP) asks us to find a minimum length
path between two points on a 2D plane while avoiding a set of polygonal obstacles. Existing …

Compressed path databases (CPDs) are a state-of-the-art approach to path planning, a core
AI problem. In the Grid-based Path Planning Competition, the CPD-based SRC path …

We want to compute geometric shortest paths in a collection of convex traversable polygons,
also known as a navigation mesh. Simple to compute and easy to update, navigation …

Shortest path planning is a fundamental building block in many applications. Hence
developing efficient methods for computing shortest paths in, eg, road or grid networks is an …

We introduce a novel approach to Compressed Path Databases, space efficient oracles
used to very quickly identify the first edge on a shortest path. Our algorithm achieves query …

We develop algorithms and data structures for the approximate Euclidean shortest path
problem amid a set of k convex obstacles in ℝ2 and ℝ3, with a total of n faces. The running …

Abstract Compressed Path Databases (CPDs) are a state-of-the-art method for path
planning. They record, for each start position, an optimal first move to reach any target …