1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2024
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…
cs.RO2024
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…
cs.RO2024★ 1 cited
MS-Mapping: Multi-session LiDAR Mapping with Wasserstein-based Keyframe Selection
Xiangcheng Hu, Jin Wu, Jianhao Jiao +2
Large-scale multi-session LiDAR mapping is crucial for various applications but still faces significant challenges in data redundancy, memory consumption, and efficiency. This pape…