4 accepted papers
This study proposes GLO, a general LiDAR-only odometry method with high efficiency and low drift. First, we propose a map data structure using multilevel voxels to improve map update efficiency. Each voxel node actively maintains plane features, minimizing redundant fitting and enhancing matching ef
Inspired by how humans perceive, remember, and understand the world, semantic graphs have become an efficient solution for place representation and location. However, many current graph-based LiDAR loop closing methods focus on extracting adjacency matrices or semantic histograms to describe the sce
This paper presents a tightly coupled pipeline, which efficiently fuses measurements of LiDAR, camera, IMU, encoder, and GNSS to estimate the robot state and build a map even in challenging situations. The depth of visual features is extracted by projecting the LiDAR point cloud and ground plane int…
In recent years, many excellent SLAM methods based on cameras, especially the camera-IMU fusion (VIO), have emerged, which has greatly improved the accuracy and robustness of SLAM. However, we find through experiments that most of the existing VIO methods perform well on drones or drone datasets, bu…