LiDAR Scan

LiDAR scanning involves acquiring 3D point cloud data of a scene using laser beams, primarily aiming for accurate scene reconstruction and object detection. Current research focuses on improving odometry and mapping accuracy through novel algorithms like those based on iterative closest point (ICP), normal distributions transform (NDT), and Kalman filtering, often incorporating inertial measurement unit (IMU) data and semantic segmentation for enhanced robustness. These advancements are crucial for applications such as autonomous navigation, 3D modeling, and high-definition map creation, driving progress in robotics, autonomous driving, and remote sensing.