Abstract Title
LiDAR Odometry and Mapping for Terrain Analysis from Drones
Abstract
Capturing accurate and highly-detailed 3D maps of terrain is a powerful tool for science. This can be accomplished using an Unmanned Aerial Vehicle (UAV) equipped with a Light Detection And Ranging (LiDAR) sensor. The resulting sensor data takes the form of point clouds with dense regions appearing along visible surfaces encountered. Existing integrated solutions allow for a UAV to follow a flight plan and capture raw point cloud data. The software to manage these solutions and run analyses varies widely in functionality and availability, however, and finding existing software to match the needs of a given research effort can be challenging. This project aims to develop such software for use in research at Idaho State University. LiDAR Odometry And Mapping (LOAM) is an advanced variation of a Simultaneous Localization And Mapping (SLAM) algorithm. Using LOAM, the UAV will return from its flights with data onboard having already been assembled into a 3D map of the environment as the the data was gathered. The capability to quickly and reliably capture these maps will facilitate the improvement of many ecosystem services.
LiDAR Odometry and Mapping for Terrain Analysis from Drones
Capturing accurate and highly-detailed 3D maps of terrain is a powerful tool for science. This can be accomplished using an Unmanned Aerial Vehicle (UAV) equipped with a Light Detection And Ranging (LiDAR) sensor. The resulting sensor data takes the form of point clouds with dense regions appearing along visible surfaces encountered. Existing integrated solutions allow for a UAV to follow a flight plan and capture raw point cloud data. The software to manage these solutions and run analyses varies widely in functionality and availability, however, and finding existing software to match the needs of a given research effort can be challenging. This project aims to develop such software for use in research at Idaho State University. LiDAR Odometry And Mapping (LOAM) is an advanced variation of a Simultaneous Localization And Mapping (SLAM) algorithm. Using LOAM, the UAV will return from its flights with data onboard having already been assembled into a 3D map of the environment as the the data was gathered. The capability to quickly and reliably capture these maps will facilitate the improvement of many ecosystem services.