  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 fresher 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 proposed for effective
online DOR. Then, in scan fresher, region-wise ground plane estimation (R-GPE)
is adopted for estimating and preserving ground information and Scan-to-Map
Removal (S2M-R) is proposed to discriminate and remove dynamic regions.
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 the state-of-the-art methods. And we also validate
the proposed framework in real-world environments.
