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Skeleton Disk-Graph Roadmap: A Sparse Deterministic Roadmap for Safe 2D Navigation and Exploration

Thibault Noël, Antoine Lehuger Lehuger, Eric Marchand, Francois Chaumette

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Abstract

In this paper, we describe a novel roadmap construction method in unknown environments, which relies on the extraction of the Hamilton-Jacobi skeleton of the free space. This skeleton is used to construct a graph of free-space bubbles, effectively compressing the skeleton information in a sparse data structure but retaining its topology. The bubbles also enforce safety directly in the roadmap structure. We first demonstrate the relevance of this approach for standard path- planning tasks. We also propose a frontiers-based exploration strategy able to autonomously and safely build a complete 2D map of the environment.

Index terms

Motion and Path Planning Autonomous Agents Reactive and Sensor-Based Planning