Magnetometer Aided GPS-free Localization of an Autonomous Vineyard Drone

Autonomous agricultural machines are attracting significant attention from the industry. Automatization helps to reduce costs, and increase productivity. This paper designs a global localization algorithm for an agricultural drone designed for autonomous operation in vineyards. Particularly, the main objective is to obtain an accurate localization also when the GPS localization fails. The scheme has to main components: an Extended Kalman Filter (EKF) and an online magnetometer calibration module. The first fuses information from a inertial sensors, track encoders and azimuth from the calibrated magnetometer. The second module adaptively estimates the magnetometer distortion parameters with a Recursive Least Square (RLS) with a forgetting factor. We validated the proposed scheme during extensive in field tests obtaining centimeter level accuracy.