LiDAR Inertial Visual Odometry

LiDAR Inertial Visual Odometry (LIVO) aims to accurately and robustly estimate the pose (position and orientation) of a moving platform by fusing data from LiDAR, inertial measurement units (IMUs), and cameras. Current research emphasizes efficient and robust algorithms, often employing direct methods that process raw sensor data without feature extraction, and tightly-coupled fusion strategies like Extended Kalman Filters or graph optimization to integrate heterogeneous sensor information. This work is significant for advancing autonomous navigation in challenging environments, particularly for robotics and autonomous vehicles, by improving localization accuracy and reliability even in the presence of sensor noise or data degeneracy.