7 papers
DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration
Xiangcheng Hu, Xieyuanli Chen, Mingkai Jia +3
LiDAR point cloud registration is fundamental to robotic perception and navigation. In geometrically degenerate environments (e.g., corridors), registration becomes ill-conditioned…
MapEval: Towards Unified, Robust and Efficient SLAM Map Evaluation Framework
Xiangcheng Hu, Jin Wu, Mingkai Jia +6
Evaluating massive-scale point cloud maps in Simultaneous Localization and Mapping (SLAM) remains challenging, primarily due to the absence of unified, robust and efficient evaluat…
FusionPortableV2: A Unified Multi-Sensor Dataset for Generalized SLAM Across Diverse Platforms and Scalable Environments
Hexiang Wei, Jianhao Jiao, Xiangcheng Hu +7
Simultaneous Localization and Mapping (SLAM) technology has been widely applied in various robotic scenarios, from rescue operations to autonomous driving. However, the generalizat…
LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation
Jianhao Jiao, Jinhao He, Changkun Liu +4
This paper presents LiteVLoc, a hierarchical visual localization framework that uses a lightweight topo-metric map to represent the environment. The method consists of three sequen…
Heterogeneous LiDAR Dataset for Benchmarking Robust Localization in Diverse Degenerate Scenarios
Zhiqiang Chen, Yuhua Qi, Dapeng Feng +6
The ability to estimate pose and generate maps using 3D LiDAR significantly enhances robotic system autonomy. However, existing open-source datasets lack representation of geometri…
MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
Xiangcheng Hu, Jin Wu, Jianhao Jiao +4
Large-scale multi-session LiDAR mapping is essential for a wide range of applications, including surveying, autonomous driving, crowdsourced mapping, and multi-agent navigation. Ho…