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
Recent advances in artificial intelligence have significantly impacted image retrieval tasks, yet Patent-Product Image Retrieval (PPIR) has received limited attention. PPIR, which retrieves patent images based on product images to identify potential infringements, presents unique challenges: (1) bot…
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…