FLASH: Fibonacci Lattice Spherical Harmonics for Semantic Place Recognition Using LiDAR

Abstract

Reliable place recognition is essential to SLAM, as it enables loop closure detection, re-localization, and map merging in long-term operation and multi-robot deployments. While semantic information enables a more human-like understanding of environments, only a few studies have integrated semantic graphs with background appearance cues. To address this gap, we propose FLASH (Fibonacci Lattice Spherical Harmonics), a novel LiDAR-based place recognition (LPR) approach that employs spherical harmonics (SH) to unify semantic, topological, and appearance information into a compact and discriminative descriptor. Specifically, FLASH introduces newly defined complementary spherical functions for the foreground and background, uniformly samples the spherical domain with a Fibonacci lattice, and expands these functions in the SH basis to obtain a rotation-invariant representation. Experimental results on KITTI, Ford Campus, Apollo, and CU-Multi demonstrate that FLASH consistently achieves higher place recognition performance across various scenarios.