activity
20242026
most citedSLABIM: A SLAM-BIM Coupled Dataset in HKUST Main Building

2 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.RO2026

RICH-SLAM: Radar SLAM with Incremental and Continuous Hilbert Mapping

Bingbing Zhang, Huan Yin, Yang Xu +4

Simultaneous localization and mapping using radar sensors has gained increasing attention due to radar's inherent robustness to adverse weather and lighting conditions. However, ra…

cs.RO2026

WaterSplat-SLAM: Photorealistic Monocular SLAM in Underwater Environment

Kangxu Wang, Shaofeng Zou, Chenxing Jiang +4

Underwater monocular SLAM is a challenging problem with applications from autonomous underwater vehicles to marine archaeology. However, existing underwater SLAM methods struggle t…

cs.RO2025

SG-Reg: Generalizable and Efficient Scene Graph Registration

Chuhao Liu, Zhijian Qiao, Jieqi Shi +3

This paper addresses the challenges of registering two rigid semantic scene graphs, an essential capability when an autonomous agent needs to register its map against a remote agen…

cs.RO20252 cited

SLABIM: A SLAM-BIM Coupled Dataset in HKUST Main Building

Haoming Huang, Zhijian Qiao, Zehuan Yu +4

Existing indoor SLAM datasets primarily focus on robot sensing, often lacking building architectures. To address this gap, we design and construct the first dataset to couple the S…

cs.RO20251 cited

GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multi-sensor Fused Odometry with Gaussian Mapping

Sheng Hong, Chunran Zheng, Yishu Shen +4

In recent years, 3D Gaussian splatting (3D-GS) has emerged as a novel scene representation approach. However, existing vision-only 3D-GS methods often rely on hand-crafted heuristi…

cs.RO2024

SLIM: Scalable and Lightweight LiDAR Mapping in Urban Environments

Zehuan Yu, Zhijian Qiao, Wenyi Liu +2

LiDAR point cloud maps are extensively utilized on roads for robot navigation due to their high consistency. However, dense point clouds face challenges of high memory consumption…