Research on deflection angle measurement system of tractor guide wheel based on GNSS/INS

doi:10.12398/j.issn.2096-7217.2024.02.004

Abstract

Abstract:

Traditional angle sensors have problems such as insufficient accuracy and complex installation and debugging when measuring the deflection angle of tractor guide wheels， which hinder the high precision and stability requirements of tractor automatic navigation operations. Therefore， this paper aims to construct and validate a novel system based on the principles of Global Navigation Satellite System （GNSS） and Inertial Navigation System （INS）， which is capable of real-time calculation of dynamic angles of the tractor's steering wheel. First， a in-depth analysis of GNSS/INS fusion principles was conducted， and corresponding GNSS/INS data measurement bench tests were designed to obtain measurement values from angle sensors. Subsequently， three filtering algorithms， namely Kalman Filter （KF）， Extended Kalman Filter （EKF）， and Unscented Kalman Filter （UKF）， were employed to filter the angle measurement values， evaluating metrics such as overshoot， response time， and stability， and the results showed that UKF performed best in this system. Second， steering and straight-line performance tests were conducted under different conditions （asphalt road and farmland） for tractor automatic navigation. In the steering performance tests， fixed measurements at different angles of 1°， 5°， and 15° were conducted， and the results showed that the response time of the two environments was the smallest at 1°， but both produced the largest overshoot. At the same time， an increase in angle demonstrated a significant reduction in steady-state error. In the straight-line automatic navigation performance tests， the maximum lateral deviations for asphalt road and farmland were 17.51 mm and 18.52 mm， respectively， with system errors of 10.45 mm （2σ） and 21.07 mm （2σ）. A comparison between the two conditions indicated superior performance metrics on asphalt road， yet both conditions met the requirements of precision， response time， and stability for automatic navigation systems， thus suitable for tractor automatic navigation operations.

Key words: GNSS/INS, tractor, steering wheel deflection angle, Kalman filter, automatic navigation

CLC Number:

S232.5

FENG Shuang, ZHANG Zhaoguo, SUN Lianzhu, WANG Fa'an, XIE Kaiting. Research on deflection angle measurement system of tractor guide wheel based on GNSS/INS[J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(2): 33-41.

Figures/Tables 16

Figure 1 System installation diagram

Figure 2 Test platform for tractor automatic navigation control system

Figure 3 Large angle right deflection filter curve

Figure 4 Large angle left deflection filter curve

Figure 5 S-Curve driving filter test results

Figure 6 Measurement result with 1° deflection

Figure 7 Measurement result with 5° deflection

Figure 8 Measurement result with 15° deflection

Table 1 Measurement results of asphalt pavement deflection system

转角角度/（°）	延迟时间/s	上升时间/s	峰值时间/s	调节时间/s	超调量/%	绝对误差/（°）	稳态误差/%
1	0.128	0.311	0.734	0.906	5.500	0.033	3.3
5	0.112	0.799	0.921	1.093	无超调	0.167	3.340
15	0.141	0.628	0.922	0.922	无超调	0.029	0.193

Table 2 Measurements of environmental deflection systems in agricultural fields

转角角度/(°)	延迟时间/s	上升时间/s	峰值时间/s	调节时间/s	超调量/%	绝对误差/(°)	稳态误差/%
1	0.162	0.450	0.547	0.547	5.400	0.083	8.300
5	0.242	0.432	0.719	1.266	0.002	0.010	0.200
15	0.134	0.526	0.719	1.453	0.780	0.235	1.566

Figure 9 Measurement result with 1° deflection

Figure 10 Measurement result with 5° deflection

Figure 11 Measurement result with 15° deflection

Figure 12 Transverse deviation diagram for asphalt pavement

Figure 13 Horizontal deviation map of farmland environment

Table 3 Deviation results for linear autopilot

	横向偏差均值/mm	横向偏差标准差/mm	横向偏差最大值/mm	直线自动导航系统误差/mm
沥青地面	5.02	8.71	17.51	10.45
农田环境	10.87	12.98	18.52	21.07

References 22

1	姚成胜，滕毅，黄琳. 中国粮食安全评价指标体系构建及实证分析［J］. 农业工程学报， 2015， 31（4）： 1-10.
	YAO Chengsheng， TENG Yi， HUANG Lin， et al. Evaluation index system construction and empirical analysis on food security in China ［J］. Transactions of the Chinese Society of Agricultural Engineering， 2015， 31（4）： 1-10.
2	郑旭媛，徐志刚. 资源禀赋约束、要素替代与诱致性技术变迁——以中国粮食生产的机械化为例［J］. 经济学（季刊）， 2017， 16（1）： 45-66.
	ZHEN Xuyuan， Zhigang XÜ. Endowment restriction， factor substitution and induced technological innovation： A case research on the grain producing mechanization in China ［J］. China Economic Quarterly， 2017， 16（1）： 45-66.
3	匡远配，易梦丹. 精细农业推进现代农业发展：机理分析和现实依据［J］. 农业现代化研究， 2018， 39（4）： 551-558.
	KUANG Yuanpei， YI Mengdan. Precision agriculture promoting the development of modern agriculture： Theoretical mechanism and practical evidence ［J］. Research of Agricultural Modernization， 2018， 39（4）： 551-558.
4	张漫，季宇寒，李世超，等. 农业机械导航技术研究进展［J］. 农业机械学报， 2020， 51（4）： 1-18.
	ZHANG Man， JI Yuhan， LI Shichao， et al. Research progress of agricultural machinery navigation technology ［J］. Transactions of the Chinese Society for Agricultural Machinery， 2020， 51（4）： 1-18.
5	王雷，赖维军. 自动导航拖拉机在精准农业上的运用［J］. 河北农机， 2021（8）： 27-28.
6	白学峰，常江雪，滕兆丽，等. 我国智能农业拖拉机关键技术研究进展［J］. 智能化农业装备学报（中英文）， 2022， 3（2）： 10-21.
	BAI Xuefeng， CHANG Jingxue， TENG Zhaoli， et al. Research progress on key technologies of intelligent agricultural tractors in China ［J］. Journal of Intelligent Agricultural Mechanization， 2022， 3（2）： 10-21.
7	刘艳亮，张海平，徐彦田，等. 全球卫星导航系统的现状与进展［J］. 导航定位学报， 2019， 7（1）： 18-21， 27.
	LIU Yanliang， ZHANG Haiping， XU Yantian， et al. Development status and trend of global navigation satellite system ［J］. Journal of Navigation Positioning， 2019， 7（1）：18-21， 27.
8	BENGOCHEA-GUEVARA J M， CONESA-MUÑOZ J， ANDÚJAR D， et al. Merge fuzzy visual servoing and GPS-based planning to obtain a proper navigation behavior for a small crop-inspection robot ［J］. Sensors， 2016， 16： 276.
9	KIM M， PARK C， YOON J. The design of GNSS/IMU loosely-coupled integration filter for wearable EPTS of football players ［J］. Sensors， 2023， 23： 1749.
10	李忠利，刘小锋，陈修魁，等. 基于信息融合的拖拉机组合导航定位系统研究［J］. 农业机械学报， 2020， 51（8）： 382-390， 399.
	LI Zhongli， LIU Xiaofeng， CHEN Xiukui， et al. Tractor integrated navigation and positioning system based on data fusion ［J］. Transactions of the Chinese Society for Agricultural Machinery， 2020，51（08）：382-390， 399.
11	钟银，薛梦琦，袁洪良. 智能农机GNSS/INS组合导航系统设计［J］. 农业工程学报， 2021， 37（9）： 40-46.
	ZHONG Yin， XUE Mengqi， YUAN Hongliang. Design of the GNSS/INS integrated navigation system for intelligent agricultural machinery ［J］. Transactions of the Chinese Society of Agricultural Engineering， 2021， 37（9）： 40-46.
12	YIN X， NOGUCHI N. Development and evaluation of a general-purpose electric off-road robot based on agricultural navigation ［J］. International Journal of Agricultural and Biological Engineering， 2014， 7（5）： 14-21.
13	YANG Y， ZHANG G， CHEN Z Z， et al. An independent steering driving system to realize headland turning of unmanned tractors ［J］. Computers and Electronics in Agriculture， 2022， 201： 107278.
14	王艳鑫，李加琪，王显，等. 轮式拖拉机转向角测量装置的研制与试验［J］. 中国农业大学学报， 2022， 27（1）： 203-211.
	WANG Yanxin， LI Jiaqi， WANG Xian， et al. Development and test of a steering angle measuring device for wheeled tractor ［J］. Journal of Agricultural University， 2022， 27（1）： 203-211.
15	何杰，高维炜，王辉，等. 基于GNSS航向微分和MEMS陀螺仪的农机轮角测量方法［J］. 华南农业大学学报， 2020， 41（5）： 91-98.
	HE Jie， GAO Weiwei， WANG Hui， et al. Wheel steering angle measurement method of agricultural machinery based on GNSS heading differential and MEMS gyroscope ［J］. Journal of South China Agricultural University， 2020， 41（5）： 91-98.
16	陈云，何艳. 基于GNSS姿态与电机编码器的农机转向角度测量系统研制［J］. 农业工程学报， 2021， 37（10）： 10-17.
	CHEN Yun， HE Yan. Development of agricultural machinery steering wheel angle measuring system based on GNSS attitude and motor encoder ［J］. Transactions of the Chinese Society of Agricultural Engineering， 2021， 37（10）： 10-17.
17	高维炜. 基于GNSS和MEMS陀螺的拖拉机自动导航前轮转向角测量方法研究［D］. 广州：华南农业大学， 2018.
	Gao Weiwei. Research of steering angle measurement of front wheel based gnss and mems gyroscope used on automatic navigation of tractor ［D］. Guangzhou： South China Agricultural University， 2018.
18	彭丁聪. 卡尔曼滤波的基本原理及应用［J］. 软件导刊， 2009， 8（11）： 32-34.
	PENG Dingcong. Pseudo-linear Kalman filter in passive target tracking ［J］. Software Guide， 2009， 8（11）： 32-34.
19	宋迎春. 动态定位中的卡尔曼滤波研究［D］. 长沙：中南大学， 2008.
	SONG Yingchun. Research on Klaman filter in kinematic positioning ［D］. Changsha： Central South University， China， 2008.
20	蔡頔. GNSS/INS组合导航数据融合算法研究［D］. 南京：南京信息工程大学， 2023.
	CAI Di. Research on GNSS/INS integrated navigation data fusion algorithm ［D］. Nanjing： Nanjing University of Information Science and Technology， 2023.
21	赵强，范思远，唐政林. 基于迭代扩展卡尔曼滤波的车辆运动状态估计［J］. 森林工程， 2021， 37（1）：66-72， 79.
	ZHAO Qiang， FAN Siyuan， TANG Zhenglin. Vehicle motion state estimation based on iterative extended Kalman filter ［J］. Forest Engineering， 2021， 37（1）： 66-72， 79．
22	孙连烛. 基于GNSS/INS的拖拉机导向轮偏转角度测量系统研究［D］. 昆明：昆明理工大学， 2020.
	SUN Lianzhu. Research on deflection angle measurement system of tractor guide wheel based on GNSS / INS ［D］. Kunming： Kunming University of Science and Technology， 2020.

[1]	YU Qiang, LI Xueyan, PAN Xinjia, HE Xionglin, FAN Wentao, WANG Fang, WANG Yu. Research on the energy control optimized strategy of electric tractor composite power supply based on improved genetic algorithm [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 14-23.
[2]	CUI Xinyu, CUI Bingbo, MA Zhen, HAN Yi, ZHANG Jianxin, WEI Xinhua. Integration of geometric-based path tracking controller and its application in agricultural machinery automatic navigation [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 24-31.
[3]	Bai Xuefeng, Chang Jiangxue, Teng Zhaoli, Lu Zhixiong. Research progress on key technologies of intelligent agricultural tractors in China [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 10-21.
[4]	Zhang Lei, Liu Yiting, Chen Guangming, Li Peijuan. Research on navigation and rectification of inspection robot based on ultrasonic sensor [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 64-70.