Attitude Estimation of Agricultural Implements Based on Quaternion and Complementary Filter

Abstract

This paper proposed a quaternion and complementary filter-based attitude estimation algorithm for agricultural implements in dynamic conditions. Built a minimal attitude estimation system using micro-electro-mechanical-system (MEMS) based sensors and STM32F446RC core-processor. The inertial measurement unit (IMU) ADIS 16445 is composed of a triaxial gyroscope and a triaxial accelerometer. Utilizing quaternion for attitude representation while combining the complementary filtering algorithm, the estimation error from the gyroscope was corrected during the data processing by the accelerometer. The experiments were conducted both on the SGT320E triaxial turntable platform and the ZP9500 self-propelled boom sprayer with the assistance of antenna positioning and attitude module BD982 in the field. The triaxial turntable platform dynamic experiment result showed that the average error of the attitude estimation was 0.15° and the maximal measurement error was 0.45°. Meanwhile the results in the field showed that the average error was 0.42° and the maximal measurement error was 0.62°, which satisfied the precise operation requirement of the agricultural equipment. The method proposed in this paper helps to reduce the costs of resources and improve the quality of precision farming especially the performance of agricultural implements.