An Acquisition Method of Agricultural Equipment Roll Angle Based on Multi-Source Information Fusion.

Yang Li,Huili Liu,Huibin Sun,Xuhui Fan,Xinliang Tian,Honglei Jia,Jiangtao Qi

doi:10.3390/s20072082

Abstract

Accurately obtaining roll angles is one of the key technologies to improve the positioning accuracy and operation quality of agricultural equipment. Given the demand for the acquisition of agricultural equipment roll angles, a roll angle monitoring model based on Kalman filtering and multi-source information fusion was established by using the MTi-300 AHRS inertial sensor (INS) and XW-GI 5630 BeiDou Navigation Satellite System (BDS), which were installed on agricultural equipment. Data of the INS and BDS were fused by MATLAB; then, Kalman filter was used to optimize the data, and the state equation and measurement equation of the integrated system were established. Then, an integrated monitoring terminal man–machine interactive interface was designed on MATLAB GUI, and a roll angle monitoring system based on the INS and BDS was designed and applied into field experiments. The mean absolute error of the integrated monitoring system based on multi-source information fusion during field experiments was 0.72°, which was smaller compared with the mean absolute errors of roll angle monitored by the INS and BDS independently (0.78° and 0.75°, respectively). Thus, the roll angle integrated model improves monitoring precision and underlies future research on navigation and independent operation of agricultural equipment.

Highlights

Intelligent agricultural machinery equipment is one key technique of modern agriculture, and its intellectualization is increasingly higher and its working width is gradually broadened
The average value of measurements from the high-precision electronic level bar was used as the reference and compared with the post-processing roll angle data from the BeiDou Navigation Satellite System (BDS)
The measurements of the roll angle imply that during the dynamic straight-line driving of the tractor, the least absolute error of the roll angle based on the BDS is 0.49◦, the maximum absolute error is 0.95◦, and the average absolute error is 0.75◦, indicating that the BDS can effectively predict the roll angle of tractors

Summary

Introduction

Intelligent agricultural machinery equipment is one key technique of modern agriculture, and its intellectualization is increasingly higher and its working width is gradually broadened. When an agricultural machine is turning or driving on a curved line in farmlands, the accurate roll angle of the implement can provide support for the control of automatic navigation agricultural vehicles [3], and it will prewarn the possible roll before climbing or descending, thereby effectively decreasing the loss of life and properties [4]. The roll angle of agricultural machine can be measured in multiple ways [5,6,7,8,9], and the commonly used method is based on inertial sensors. Inertial sensors generally include accelerometers and gyroscopes [10,11,12,13] or inclination sensors [14,15].

Methods

Results

Conclusion