5 citations · 5 across the 4 of their papers we have counts for
6 papers
Flying through cluttered and dynamic environments with LiDAR
Huajie Wu, Wenyi Liu, Yunfan Ren +5
Navigating unmanned aerial vehicles (UAVs) through cluttered and dynamic environments remains a significant challenge, particularly when dealing with fast-moving or sudden-appearin…
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…
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…
Large-Scale LiDAR Consistent Mapping using Hierachical LiDAR Bundle Adjustment
Xiyuan Liu, Zheng Liu, Fanze Kong +1
Reconstructing an accurate and consistent large-scale LiDAR point cloud map is crucial for robotics applications. The existing solution, pose graph optimization, though it is time-…
BALM: Bundle Adjustment for Lidar Mapping
Zheng Liu, Fu Zhang
A local Bundle Adjustment (BA) on a sliding window of keyframes has been widely used in visual SLAM and proved to be very effective in lowering the drift. But in lidar SLAM, BA met…
Low-cost Retina-like Robotic Lidars Based on Incommensurable Scanning
Zheng Liu, Fu Zhang, Xiaoping Hong
High performance lidars are essential in autonomous robots such as self-driving cars, automated ground vehicles and intelligent machines. Traditional mechanical scanning lidars off…