LiDAR Inertial Odometry

LiDAR Inertial Odometry (LIO) aims to accurately estimate the pose and velocity of a moving platform by fusing data from a Light Detection and Ranging (LiDAR) sensor and an Inertial Measurement Unit (IMU). Current research emphasizes improving robustness and efficiency, focusing on advanced filtering techniques like Extended Kalman Filters and Iterated Extended Kalman Filters, as well as novel data association methods and uncertainty modeling to handle challenging environments and sensor limitations. The development of accurate and computationally efficient LIO systems is crucial for applications such as autonomous driving, robotics, and augmented reality, enabling reliable navigation and mapping in diverse and often challenging conditions.