Raymoval: Raycasting-based Dynamic Object Removal for Static 3D Mapping

TL;DR

This paper introduces Raymoval, a raycasting-based module that effectively removes dynamic objects from 3D maps, enhancing their static consistency for robot navigation.

Contribution

It presents a novel raycasting approach with multiple validation steps to improve dynamic object removal in static 3D mapping.

Findings

Achieves lower residual dynamics in static maps.

Reduces over-removal of static points.

Demonstrates consistent results on SemanticKITTI and custom datasets.

Abstract

Static mapping is fundamental to robot navigation, providing a persistent geometric prior and a consistent reference for long-term autonomy. However, dynamic objects leave residual traces and cause surface loss, which reduces map consistency. We propose a raycasting-based module for dynamic object removal in static 3D mapping. Each scan is projected onto an azimuth-elevation grid, and for every viewing direction we compare the bin-wise minimum range with the map's first-hit distance computed by raycasting. Furthermore, we apply a raycast consistency test that separates dynamic from static points. Finally, a spatial consistency validation step refines labels, producing static maps with lower residual dynamics and reduced over-removal. We evaluate our approach quantitatively and qualitatively on SemanticKITTI and a challenging custom dataset, and show consistent static mapping results.