Quick Heuristic Validation of Edges in Dynamic Roadmap Graphs

TL;DR

This paper presents a fast heuristic approach for validating edges in dynamic robot motion planning graphs, improving accuracy and efficiency in semi-lazy roadmap updates in changing environments.

Contribution

Introduces the Red-Green-Gray paradigm, a novel heuristic method for classifying roadmap edges in dynamic environments, enhancing update speed and accuracy.

Findings

Increased accuracy over existing methods

Able to correctly identify invalid edges

Maintains comparable update runtimes

Abstract

In this paper we tackle the problem of adjusting roadmap graphs for robot motion planning to non-static environments. We introduce the "Red-Green-Gray" paradigm, a modification of the SPITE method, capable of classifying the validity status of nodes and edges using cheap heuristic checks, allowing fast semi-lazy roadmap updates. Given a roadmap, we use simple computational geometry methods to approximate the swept volumes of robots and perform lazy collision checks, and label a subset of the edges as invalid (red), valid (green), or unknown (gray). We present preliminary experimental results comparing our method to the well-established technique of Leven and Hutchinson, and showing increased accuracy as well as the ability to correctly label edges as invalid while maintaining comparable update runtimes.