7 citations · 7 across the 3 of their papers we have counts for
5 papers · 1 filter
Accelerating Large-scale Bundle Adjustment for LiDAR Mapping via Parallel Computing
Yixi Cai, Rundong Li, Yuhan Xie +3
LiDAR bundle adjustment is widely utilized in mapping to construct globally consistent point cloud maps. In this paper, we propose the first fully parallel computing framework to a…
A Survey on LiDAR-based Autonomous Aerial Vehicles
Yunfan Ren, Yixi Cai, Haotian Li +6
This survey offers a comprehensive overview of recent advancements in LiDAR-based autonomous Unmanned Aerial Vehicles (UAVs), covering their design, perception, planning, and contr…
Efficient and Distributed Large-Scale Point Cloud Bundle Adjustment via Majorization-Minimization
Rundong Li, Zheng Liu, Hairuo Wei +3
Point cloud bundle adjustment is critical in large-scale point cloud mapping. However, it is both computationally and memory intensive, with its complexity growing cubically as the…
Voxel-SLAM: A Complete, Accurate, and Versatile LiDAR-Inertial SLAM System
Zheng Liu, Haotian Li, Chongjian Yuan +7
In this work, we present Voxel-SLAM: a complete, accurate, and versatile LiDAR-inertial SLAM system that fully utilizes short-term, mid-term, long-term, and multi-map data associat…
LVBA: LiDAR-Visual Bundle Adjustment for RGB Point Cloud Mapping
Rundong Li, Xiyuan Liu, Haotian Li +4
Point cloud maps with accurate color are crucial in robotics and mapping applications. Existing approaches for producing RGB-colorized maps are primarily based on real-time localiz…