LiDAR Mapping

LiDAR mapping uses light detection and ranging to create detailed 3D maps of environments, primarily aiming for accurate and efficient scene reconstruction. Current research emphasizes developing robust methods for handling dynamic objects and large-scale scenes, often employing neural implicit representations (like Neural Radiance Fields and their variants), octree structures for efficient data management, and bundle adjustment techniques for improved accuracy. These advancements are crucial for applications such as autonomous navigation, robotics, and precision agriculture, enabling more reliable and efficient operation in complex environments.