3 accepted papers
The online calibration of 4D millimeter-wave radar and camera is crucial for advancing perception and SLAM technologies in complex environments. It eliminates the reliance on manual labeling, offering real-time and convenience. However, the sparse nature of 4D radar point clouds presents challenges
LiDAR-based simultaneous localization and mapping (SLAM) is crucial for achieving accurate pose estimation and map generation, thus serving as a foundational technology in the advancement of autonomous driving systems. In this letter, we introduce an accurate and robust feature-based LiDAR odometry
Point cloud registration is a fundamental task in various intelligence applications, including simultaneous localization and mapping as well as scene reconstruction. However, in large-scale scenes, the majority of point clouds exhibit partial overlap, posing a significant challenge to the registrati