Method for measuring the steering wheel angle of paddy field agricultural machinery by integrating RTK-GNSS and dual-MEMS gyroscope

Authors

  • Pei Wang 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China; 4. Maoming Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Maoming 525000, Guangdong, China
  • Lian Hu 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China; 4. Maoming Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Maoming 525000, Guangdong, China
  • Jie He 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China; 4. Maoming Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Maoming 525000, Guangdong, China
  • Siqi Ke Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China
  • Zhongxian Man 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • Tuanpeng Tu 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • Luning Yang 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • Yuanyuan Li 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • YangLing Yi 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • Weicong Li 1. College of Engineering, South China Agricultural University/Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; 2. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 3. Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China
  • Xiwen Luo

DOI:

https://doi.org/10.25165/ijabe.v15i6.7523

Keywords:

steering wheel angle, MEMS gyroscope, Kalman filter, agricultural machinery navigation, agricultural machinery

Abstract

Aiming at the application environment of paddy agricultural machinery with bumpy and undulating changes, the problems affecting the method for steering wheel angle measurement by MEMS gyroscope were analyzed, and a wheel angle measurement method combining Dual-MEMS gyroscope (dual MEMS gyroscope) and RTK-GNSS was designed. The adaptive weighting method was used to fuse the heading angle differentiation of RTK-GNSS, the MEMS gyroscope angle rate, and velocity data, and the rod-arm compensation was performed to accurately obtain the angle rates of the body and steering wheels of agricultural machinery; the difference between the combined angular rate of the steering wheel of the agricultural machinery and the angular rate of the agricultural machinery body was obtained, and the integrator is used to integrate the difference to get the wheel steering angle value, and the Kalman filter was designed to make feedback correction for the integration process of angle calculation to eliminate the errors caused by the gyroscope zero bias, random drift, and gyroscope rod arm effect, and to obtain the accurate value of wheel steering angle. A comparative test with the connecting rod wheel angle sensor was designed, and the results show that the maximum deviation is 4.99°, the average absolute average value is 1.61°, and the average standard deviation is 0.98°. The method in this study and the connecting rod wheel angle sensor were used on paddy farm machinery. The wheel angle measurement deviation of the proposed method and the connecting rod wheel angle sensor was not more than 1°, which is relatively small. It has good stability, speed adaptability, and dynamic responsiveness that meets the accuracy requirements of steering wheel angle measurement for paddy field agricultural machinery unmanned driving and can be used instead of connecting rod angle sensors for unmanned agricultural machinery. Keywords: steering wheel angle, MEMS gyroscope, Kalman filter, agricultural machinery navigation, agricultural machinery DOI: 10.25165/j.ijabe.20221506.7523 Citation: Wang P, Hu L, He J, Ke S Q, Man Z X, Tu T P, et al. Method for measuring the steering wheel angle of paddy field agricultural machinery by integrating RTK-GNSS and dual-MEMS gyroscope. Int J Agric & Biol Eng, 2022; 15(6): 197–205.

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Published

2022-12-27

How to Cite

Wang, P., Hu, L., He, J., Ke, S., Man, Z., Tu, T., … Luo, X. (2022). Method for measuring the steering wheel angle of paddy field agricultural machinery by integrating RTK-GNSS and dual-MEMS gyroscope. International Journal of Agricultural and Biological Engineering, 15(6), 197–205. https://doi.org/10.25165/ijabe.v15i6.7523

Issue

Vol. 15 No. 6 (2022): IJABE

Section

Information Technology, Sensors and Control Systems

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