Robust Localization and Localizability Prediction Using a Rotating Laser Scanner

摘要

A robust localization approach for UAVs that fuses measurements from inertial measurement unit (IMU) and a rotating laser scanner is described. An Error State Kalman Filter (ESKF) is used for sensor fusion and is combined with a Gaussian Particle Filter (GPF) for measurements update. Additionally, a new method to evaluate localizability of a given 3D map is described to show that the computed localizability can precisely predict localization errors, thus helping to find safe routes during flight.