Multi-Session, Localization-Oriented and Lightweight LiDAR Mapping Using Semantic Lines and Planes
Zehuan Yu,Zhijian Qiao,Liuyang Qiu,Huan Yin,Shaojie Shen,Zehuan Yu,Zhijian Qiao,Liuyang Qiu,Huan Yin,Shaojie Shen
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 widely used point clouds. The proposed framework achieves consistent mapping in a coarse-to-fine manner. Global place recognition is achieved by associating lines and planes on the Grassmannian manifold, followed by an outli...
