Work

GNSS/LiDAR-SLAM with Depth Image-based Scan Matching for Waterborne Mobile Mapping

Year: 2025

Type: article

Abstract: . In this research, we propose a methodology to improve the performance of scan matching and point cloud segmentation for 3D mapping of urban river environments. We also focus on the integration of depth image-based scan matching and spatial segmentation using streaming LiDAR data embedded in GNSS/LiDAR-SLAM. Moreover, we conduct experiments using a waterborne mobile mapping system to verify that our methodology can improve the stability and scalability of point cloud processing and achieve high-speed processing even in measured environments that cause SLAM degeneration problems. In addition, we propose a fast object classification based on rule-based segmentation using streaming point clouds.

Source: The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences

DOI: 10.5194/isprs-archives-xlviii-4-w15-2025-121-2025

Authors: Masafumi Nakagawa, Nobuaki Kubo, Etsuro Shimizu

Institutions: Shibaura Institute of Technology, Tokyo University of Marine Science and Technology

Language: English

Topic: Robotics and Sensor-Based Localization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: diamond

OpenAlex ID: W4414317414