基于双观测值融合卡尔曼滤波器的水田农机转向轮角估计方法与试验  

Estimation Method and Experiment of Wheel Angle of Paddy Field Agricultural Machinery Based on Dual Observation Fusion Kalman Filter

作　　者：满忠贤 何杰[1,2] 冯达文 李仁浩 邓小兵 涂团鹏 汪沛 胡炼[1,2] MAN Zhongxian;HE Jie;FENG Dawen;LI Renhao;DENG Xiaobing;TU Tuanpeng;WANG Pei;HU Lian(Key Laboratory of Key Technology on Agricultural Machine and Equipment,Ministry of Education,South China Agricultural University,Guangzhou 510642,China;State Key Laboratory of Agricultural Equipment Technology,Guangzhou 510642,China)

机构地区：[1]华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642 [2]农业装备技术全国重点实验室,广州510642

出　　处：《农业机械学报》2025年第2期38-47,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2021YFD2000600)。

摘　　要：针对水田自动驾驶农机遇到侧滑时速度突变导致转角估计不准确的问题,本文提出了一种基于双观测值融合卡尔曼滤波器的水田作业农机转向轮角估计方法,建立了水田作业农机转向轮角估计模型。首先采用改进型两轮农机侧滑模型获得基于运动学模型的水田农机前轮转向角度,其次对所采集的GPS速度和惯性导航速度采用加权观测融合的方法对转向模型的水田农机作业速度进行补偿,最后提出了基于双观测值融合卡尔曼滤波器的水田作业农机轮向轮角估计方法,将基于运动学模型的前轮转向角和基于转向电机编码的前轮转向角作为双观测值,从而估计水田农机前轮转角。为验证本文所提方法,以水稻直播机为研究平台,在水田中开展速度校正、前轮转向角估计试验和直线跟踪试验。速度校正试验结果表明,水田硬底层高低不平是前轮转角拟合精度不佳的直接原因,本文所提方法将直播机速度稳定在一定范围内,解决了因水田硬底层起伏变化造成前轮转角拟合精度不佳的问题。前轮转向角估计试验结果表明,农机前轮估计角度相对角度传感器角度变化跟踪误差平均值为0.12°,偏差最大值为1.67°,偏差标准差为0.4°。本文所提方法能够准确地测量农机前轮转向角,最终控制直播机稳定追踪目标角度,满足水田农机前轮转角估计精度要求。直线跟踪试验结果表明,在水田环境下,平均绝对误差为3.14 cm,位置偏差标准差为2.11 cm。本文提出的方法适用于水田无人驾驶,提高了转角估计精度和农机导航作业质量。In order to solve the problem that the sudden change of the speed of automatic driving agricultural machinery in paddy field leads to inaccurate angle estimation,a steering wheel angle estimation method of agricultural machinery in paddy field was proposed based on dual observation fusion Kalman filter,and a steering wheel angle estimation model of agricultural machinery in paddy field was established.Firstly,the improved two-wheeled agricultural machinery sideslip model was used to obtain the front wheel steering angle of paddy agricultural machinery based on kinematics model.Secondly,the collected GPS speed and inertial navigation speed were compensated by weighted observation fusion method.Finally,a method for estimating the front wheel steering angle of paddy agricultural machinery based on dual observation fusion Kalman filter was proposed,which took the front wheel steering angle based on kinematics model and the front wheel steering angle based on steering motor coding as dual observation values,so as to estimate the front wheel steering angle of paddy agricultural machinery.In order to verify the proposed method,speed correction,front wheel steering angle estimation test and linear tracking test were carried out in paddy field on the platform of rice direct seeding machine.The results of speed correction test showed that the unevenness of paddy field hard bottom layer was the direct reason for the poor fitting accuracy of front wheel angle.The proposed method stabilized the speed of direct seeding machine in a certain range,and solved the problem of poor fitting accuracy of front wheel angle caused by the fluctuation of paddy field hard bottom layer.The front wheel steering angle estimation experiment showed that the average tracking error of the virtual wheel angle relative to the angle change of the angle sensor was 0.12°,the maximum deviation was 1.67°and the standard deviation was 0.4°.The method can accurately measure the steering angle of the front wheel of agricultural machinery,and finally cont

关 键 词：水田 农业机械 自动驾驶 卡尔曼滤波器 

分 类 号：S220[农业科学—农业机械化工程] S24[农业科学—农业工程]