Point-LIO: Robust High-Bandwidth LiDAR-Inertial Odometry

Github: github.com/hku...
Paper: onlinelibrary....
Point-LIO has two key novelties that enable a high-bandwidth LiDAR-inertial odometry (LIO). The first one is a point-by-point LIO framework, where the state is updated at each LiDAR point measurement without accumulating them into a frame. This point-by-point update allows an extremely high-frequency odometry output, significantly increases the odometry bandwidth, and also fundamentally removes the artificial in-frame motion distortion in aggressive motions. The second main novelty is a stochastic process-augmented kinematic model which models the IMU measurements as an output, instead of input as in existing filter-based odometry or SLAM systems, of the model. This new modeling method enables accurate localization and reliable mapping for aggressive motions even when IMU measurements are saturated. To be noted, the 'No Prior Map' label in the video means that the video is recorded from the very beginning of the system.