Flydar: Magnetometer-based High Angular Rate Estimation during Gyro Saturation for SLAM

In this paper, the high angular rate estimation for simultaneous localisation and mapping (SLAM) of a Flying Li-DAR (Flydar) is presented. The proposed EKF-based algorithm exploits the sinusoidal magnetometer measurement generated by the continuously rotating airframe for estimation of the robot hovering angular velocity. Significantly, the proposed method does not rely on additional sensors other than existing IMU sensors already being used for flight stabilization. The gyro measurement and the gyro bias are incorporated as a control input and a filter state respectively to enable estimation even under gyro saturation condition. Additionally, this work proposes leveraging on the inherently rotating locomotion to generate a planar lidar scan using only a single-point laser for possible lightweight autonomy. The proposed estimation method was experimentally evaluated on a ground rotating rig up to twice the gyro saturation limit with an effective rms error of 0.0045Hz; and on the proposed aerial platform - Flydar - hovering beyond the saturation limit with a rms error of 0.0056Hz. Lastly, the proposed method for SLAM using the rotating dynamics of Flydar was demonstrated with a localisation accuracy of 0.11m.