FAST-LIO2: Fast Direct LiDAR-inertial Odometry
FAST-LIO
FAST-LIO (Fast LiDAR-Inertial Odometry) is a computationally efficient and robust LiDAR-inertial odometry package. It fuses LiDAR feature points with IMU data using a tightly-coupled iterated extended Kalman filter to allow robust navigation in fast-motion, noisy or cluttered environments where degeneration occurs. Our package address many key issues:
- Fast iterated Kalman filter for odometry optimization;
- Automaticaly initialized at most steady environments;
- Parallel KD-Tree Search to decrease the computation;
FAST-LIO 2.0 (2021-07-05 Update)
Related video: FAST-LIO2, FAST-LIO1
FAST-LIO 2.0 Features:
- Incremental mapping using ikd-Tree, achieve faster speed and over 100Hz LiDAR rate.
- Direct odometry (scan to map) on Raw LiDAR points (feature extraction can be disabled), achieving better accuracy.
- Since no requirements for feature extraction, FAST-LIO2 can support many types of LiDAR including spinning (Velodyne, Ouster) and solid-state (Livox Avia, Horizon, MID-70) LiDARs, and can be easily extended to support more LiDARs.
- Support external IMU.
- Support ARM-based platforms including Khadas VIM3, Nivida TX2, Raspberry Pi 4B(8G RAM).