RH-Map: Online Map Construction Framework of Dynamic Object Removal Based on 3D Region-Wise Hash Map Structure

Mobile robots navigating in outdoor environments frequently encounter the issue of undesired traces left by dynamic objects and manifested as obstacles on map, impeding robots from achieving accurate localization and effective navigation. To tackle the problem, a novel map construction framework based on 3D region-wise hash map structure (RH-Map) is proposed, consisting of front-end scan refresh and back-end removal modules, which realizes real-time map construction and online dynamic object removal (DOR). First, a two-layer 3D region-wise hash map structure of map management is employed for effective online DOR. Then, in scan refresh, region-wise ground plane estimation (R-GPE) is proposed for incrementally estimating and preserving ground information, and Scan-to-Map Removal (S2M-R) is proposed to discriminate and remove dynamic objects. Moreover, the lightweight back-end removal module maintaining keyframes is proposed for further DOR. As experimentally verified on SemanticKITTI, our proposed framework yields promising performance on online DOR of map construction compared with state-of-the-art methods. We also validate the proposed framework in real-world environments.