FC-Planner: A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes

TL;DR

FC-Planner is a skeleton-guided framework that enables fast, efficient, and high-quality aerial coverage of complex 3D scenes by decomposing scenes and parallel planning, significantly outperforming existing methods.

Contribution

The paper introduces a novel skeleton-guided planning framework that decomposes scenes and enables parallel, efficient coverage path planning without pre-processing.

Findings

Over 10 times faster computation than state-of-the-art methods

Shorter coverage paths achieved

More complete coverage in complex scenes

Abstract

3D coverage path planning for UAVs is a crucial problem in diverse practical applications. However, existing methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex scenes. To address these challenges, we propose FC-Planner, a skeleton-guided planning framework that can achieve fast aerial coverage of complex 3D scenes without pre-processing. We decompose the scene into several simple subspaces by a skeleton-based space decomposition (SSD). Additionally, the skeleton guides us to effortlessly determine free space. We utilize the skeleton to efficiently generate a minimal set of specialized and informative viewpoints for complete coverage. Based on SSD, a hierarchical planner effectively divides the large planning problem into independent sub-problems, enabling parallel planning for each subspace. The carefully designed global and local planning strategies are then incorporated to guarantee both high quality and efficiency in path generation. We conduct extensive benchmark and real-world tests, where FC-Planner computes over 10 times faster compared to state-of-the-art methods with shorter path and more complete coverage. The source code will be made publicly available to benefit the community. Project page: https://hkust-aerial-robotics.github.io/FC-Planner.