Positioning and Attitude determination for Precision Agriculture Robots based on IMU and Two RTK GPSs Sensor Fusion

Abstract

This paper focuses on the development of a data fusion architecture for positioning and attitude estimation of an autonomous agricultural vehicle combining two RTK-GNSS and an Inertial Measurement Unit (IMU) system. The main algorithm steps are presented giving a generic approach for real-time vehicle guidance applications or localization using data fusion. Important features such as sensor error modeling based on the Allan variance method as well as compensation phenomena related to terrestrial navigation using IMU mechanization are presented. A loosely coupled fusion architecture is proposed allowing low complexity for realtime algorithm integration. Finally, results based on real data from a real prototype are exploited to show the efficiency of the proposed algorithm.