what is fast_lio fr?

FAST-LIO is a research software package for robots and autonomous vehicles that need to know where they are in space while moving. It combines data from two types of sensors: a LiDAR, which uses laser pulses to build a 3D map of the surroundings, and an IMU (inertial measurement unit), which measures acceleration and rotation. By fusing these two data streams, the system can track the robot's position and orientation in real time, even in environments where GPS is unavailable. The software is designed to work fast enough for real-world use. It uses a mathematical technique called an iterated extended Kalman filter to continuously refine its position estimate as new sensor readings arrive. A data structure called an incremental KD-tree is used to search the growing map quickly, which allows the system to process LiDAR scans at over 100 times per second on capable hardware. FAST-LIO 2.0, the current version, works directly on raw point cloud data rather than requiring the sensor readings to be pre-processed into features first. This makes it compatible with a wider range of LiDAR hardware, including spinning types like Velodyne and solid-state types like Livox Avia. It can also run on smaller ARM-based computers commonly used in drones and mobile robots. The package runs inside the ROS robotics middleware, which is the standard software framework for robot development in research. Setup requires Ubuntu Linux, ROS, and a few supporting libraries. A Docker container is available for those who want a pre-configured environment. This is an academic research release from the MARS Lab at the University of Hong Kong. Two research papers accompany the code.