Publications (10)
H2-Mapping: Real-time Dense Mapping Using Hierarchical Hybrid Representation
Chenxing Jiang, Hanwen Zhang, Peize Liu +4
Constructing a high-quality dense map in real-time is essential for robotics, AR/VR, and digital twins applications. As Neural Radiance Field (NeRF) greatly improves the mapping pe…
Multi-Session, Localization-oriented and Lightweight LiDAR Mapping Using Semantic Lines and Planes
Zehuan Yu, Zhijian Qiao, Liuyang Qiu +2
In this paper, we present a centralized framework for multi-session LiDAR mapping in urban environments, by utilizing lightweight line and plane map representations instead of wide…
Pyramid Semantic Graph-based Global Point Cloud Registration with Low Overlap
Zhijian Qiao, Zehuan Yu, Huan Yin +1
Global point cloud registration is essential in many robotics tasks like loop closing and relocalization. Unfortunately, the registration often suffers from the low overlap between…
CSMapping: Scalable Crowdsourced Semantic Mapping and Topology Inference for Autonomous Driving
Zhijian Qiao, Zehuan Yu, Tong Li +3
Crowdsourcing enables scalable autonomous driving map construction, but low-cost sensor noise hinders quality from improving with data volume. We propose CSMapping, a system that p…
Speak the Same Language: Global LiDAR Registration on BIM Using Pose Hough Transform
Zhijian Qiao, Haoming Huang, Chuhao Liu +4
Light detection and ranging (LiDAR) point clouds and building information modeling (BIM) represent two distinct data modalities in the fields of robot perception and construction.…
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…