Improved inclination correction method applied to the guidance system of agricultural vehicles

Ricardo Ospina, Noboru Noguchi

Abstract


This research introduces a new inclination correction method with increased accuracy applied to the guidance system of an agricultural vehicle. The method considers the geometry of a robot tractor and uses an Inertial Measurement Unit (IMU) to correct the lateral error of the RTK-GPS antenna measurements raised by the tractor's inclinations. A parameters optimization experiment and an automatic guidance experiment under real working conditions were used to compare the accuracy of a traditional correction method with the new correction method, by calculating the RMSE of the lateral error and the error reduction percentage. An additional tuned correction method was found by using a simple analytical method to find the optimal variables that reduced the lateral error to a minimum. The results indicate that the new correction method and the tuned correction method display a significant error reduction percentage compared to the traditional correction method. The methods could correct the GPS lateral error caused by the roll inclinations in real-time. The resulting lateral deviation caused by the tractor's inclinations could be reduced up to 23% for typical travelling speeds.
Keywords: inclination correction method, guidance system, agricultural vehicles, robot tractor, IMU, RTK-GPS, precision farming
DOI: 10.25165/j.ijabe.20201306.6012

Citation: Ospina R, Noguchi N. Improved inclination correction method applied to the guidance system of agricultural vehicles. Int J Agric & Biol Eng, 2020; 13(6): 183–194.

Keywords


inclination correction method, guidance system, agricultural vehicles, robot tractor, IMU, RTK-GPS, precision farming

Full Text:

PDF

References


Coulmas F. Population decline and ageing in Japan - The social consequences. New York: Ed. Routledge, 2007; 168p.

Kondo N, Monta M, Noguchi N. Agricultural robots: mechanisms and practice. Kyoto: University Press and Trans Pacific Press, 2011; 348p.

Zhang Z, Noguchi N, Ishii K. Development of a robot combine harvester. Journal of the Japanese Society of Agricultural Machinery and Food Engineers, 2015; 77(1): 45–50.

Takai R, Yang L, Noguchi N. Development of crawler-type robot tractor based on GNSS and IMU. IFAC Proceedings Volumes, 2013; 46(4): 95–98.

Lahtinen J. How mems sensors linked to GPS systems boost crop yields. eeNews Embedded. 2015. Available: https://www.eenewsembedded.com/blog/how-mems-sensors-linked-gps-systems-boost-crop-yields. Accessed on [2020-06-20].

Ryu J, Rossetter E J, Gerdes J C. Vehicle sideslip and roll parameter estimation using GPS. AVEC 2002 6th Int. Symposium on Advanced Vehicle Control, Hiroshima, Japan, 2002; pp.373–380.

Bae H S, Ryu J, Gerdes C. Road grade and vehicle parameter estimation for longitudinal control using GPS. Proceedings of the IEEE Conference on Intelligent Transportation Systems, August 2001. Oakland: IEEE. 2001; pp.166–171.

Germann S T, Isermann R. Determination of the centre of gravity Height of a vehicle with parameter estimation. IFAC Proceedings Volumes, 1994; 27(8): 563–568.

Ospina R, Noguchi N. Determination of tire dynamic properties: application to an agricultural vehicle. EAEF, 2016; 9: 123–130.

Wong J Y. Theory of ground vehicles, Second Ed. New York: John Wiley & Sons, Inc. 1993; 435p.

Liljedahl J B, Turnquist P K, Smith D W, Hoki M. Tractors and their

power units, fourth ed. New York: Van Nostrand Reinhold, 1989; pp.303–306.

Kim Y, Noh J, Shin S, Kim B, Hong S. Improved method for determining the height of center of gravity of agricultural tractors. Journal of Biosystems Engineering, 2016; 41(3): 170–176.

Al-Rawashdeh Y M, Elshafei M, Al-Malki M F. In-flight estimation of center of gravity position using all-accelerometers. Sensors, 2014; 14: 17567–17585.

Deng Z, Chu D, Tian F, He Y, Wu C, Hu Z, et al. Online estimation for vehicle center of gravity height based on unscented Kalman filter. 2017 4th International Conference on Transportation Information and Safety (ICTIS), Banff: IEEE, 2017; pp.33–36.

Claar P, Buchele W, Marley S, Sheth P. Agricultural tractor chassis suspension system for improved ride comfort. SAE Technical Paper, 1980; 801020. doi: 10.4271/801020.

Ruitao G, Yang W, Zhou Y, Hong J, Zhixiang L, Jian S. Tractor driving seat suspension system research status and strategies in China: A review. IFAC-PapersOnLine, 2018; 51(17): 576–581.

Han X, Kim H J, Jeon C W, Moon H C, Kim J H, Yi S Y. Application of a 3D tractor-driving simulator for slip estimation-based path-tracking control of auto-guided tillage operation. Biosystems Engineering, 2019; 178: 70–85.

Mizushima A, Noguchi N, Ishii K, Terao H. Position correction of vehicle inclination for agricultural vehicle guidance system. Journal of the Japanese Society of Agricultural Machinery, 1999; 61(Supp): 559–560.

Inoue K, Ootsuka K, Sugimoto M, Murakami N, Li W. Sensor fusion techniques for automatic guidance by the method of Kalman filter using DGPS and gyrocompass (Part 1). Journal of the Japanese Society of

Agricultural Machinery, 1999; 61(4): 103–113. (In Japanese)

Noguchi N. Agricultural vehicle robot. Journal of Robotics and Mechatronics, 2018; 30(2): 165–172.

Terao H, Noguchi N, Ishii K. Development of agricultural field robot in AVSE, Hokkaido University, Japan. Proc. IV International Conference “Microprocessor Systems in Agriculture”, PW Plock, Poland, 2001; pp.211–219.

Mizushima A, Ishii K, Noguchi N, Matsuo Y, Lu R. Development of a low-cost attitude sensor for agricultural vehicles. Computers and Electronics in Agriculture, 2011; 76(2): 198–204.

CAD Library of free DWG Blocks and premium AutoCAD drawings. 2019. Available: https://cad-block.com/. Accessed on [2020-06-27].

Tofael A. Navigation of an autonomous tractor using multiple sensors. PhD dissertation. Tsukuba: University of Tsukuba, 2006; 183p.

Larson D L, Smith D W, Liljedahl J B. The dynamics of three-dimensional tractor motion. Trans. of ASABE1976; 19: 195-200.

Deere & Company. John Deere Factory shipping weights and dimensions for 30 series tractors. Deere & Company. 2013. http://www.deere.com/en_US/ag/servicesupport/tips/tractors/common_stories/pf_weights_dimensions.html. Accessed on [2020-06-29].

MATLAB. Version 8.1.0.604 (R2013a). Natick, Massachusetts: The MathWorks Inc., 2013.

Murphy D J. Tractor Stability and Instability. PennState Extension, 2016. https://extension.psu.edu/tractor-stability-and-instability. Accessed on [2020-06-30].

Yang L, Noguchi N. Human detection for a robot tractor using omni-directional stereo vision. Computers and Electronics in Agriculture, 2012; 89: 116–125.




Copyright (c) 2020 International Journal of Agricultural and Biological Engineering

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

2023-2026 Copyright IJABE Editing and Publishing Office