田间作业车辆外部加速度辨识与姿态测量系统研制
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摘要
复杂田间作业环境与精细作业效果要求农机装备具备实时精准感知农机具姿态的能力,田间作业时普遍存在的车辆外部加速度对此带来挑战。为进一步提高农机装备作业质量,该文以6轴微惯性传感器为硬件传感器,以方向余弦矩阵法进行姿态解算,基于一阶外部加速度模型设计卡尔曼滤波融合算法,实现动态情况下田间作业车辆外部加速度辨识与姿态精准估计。分别采用Innova 2100型摇床与装配有MTi300航向姿态参考模块的高地隙喷雾机对系统进行试验验证。摇床试验结果表明:在外部加速度小于10g情况下,系统对外部加速度辨识误差小于0.214 m/s2;田间作业高地隙喷雾机试验结果表明,相比于MTi300,横滚角最大误差为0.23?,俯仰角最大误差为0.39?。说明该文研制姿态测量系统可准确辨识外部加速度与测量姿态,研究结果可为满足精细农业作业要求的姿态测量系统研发提供依据。
The development of precision agriculture,intelligent agricultural machinery and equipment are an effective way to alleviate the current tense situation in world food security.The complex field environment and meticulous work effects require the agricultural machinery to have the ability to perceive the attitude of the agricultural machinery accurately in real time.For example,the precision navigation control and the leveling control of agricultural implements are all dependent on the accurate measurement of attitude.What's more,the attitude of agricultural implements is one of the key parameters of agricultural mechanics modeling and agricultural implements safety warning learning.However,the external acceleration of the vehicle,which is generally present under dynamic operation conditions,poses a challenge.In order to further improve the precision operation of agricultural machinery and equipment,the paper developed a minimal hardware system for external acceleration identification and attitude estimation used for field working vehicles,and verified by the experiments taken place on the Innova 2100 shaker and the ZP9500 high level sprayer in the field.Modern micro-electromechanical systems(MEMS) technologies provide the moderate-cost and miniaturized solutions for the development of attitude reference system.By using of highly-integrated inertial measurement units(IMUs) ADIS16445 provided by ADI company and micro ARM processor STM32 F446 provided by ST company,the hardware platform was built.ADIS16445 ISensor? included tri-axial gyroscopes and tri-axial accelerometers,the raw sensors data was sampled by STM32 F446 RC processor through SPI interface.The attitude calculation was carried out based on the direction cosine matrix algorithm.Based on the gyroscope and accelerometer measurement model,an one order external acceleration measurement model was proposed,and a Kalman filter fusion algorithm with 4 state vectors was established.Since the bias of gyroscopes and accelerometers was stable after hardware preheated,the impact of bias of MEMS inertial sensors in the fusion algorithm was not considered.Innova 2100 shaker is a standard equipment of rotary motion,by setting different rotation speed,different centripetal accelerations can be achieved to verify the external acceleration identification.Innova 2100 shaker test results showed that the measure error was less than 0.214 m/s2 under the external acceleration lower than 10 g.Field experiments were conducted on Innova 2100 shaker and the ZP9500 high level sprayer provided by LOVOL company with the assistance of attitude and position reference system(AHRS) MTi300 provided by Xsens company.The MTi300 AHRS provide high precision attitude and heading output with high stability and fast dynamic response with dynamic measurement accuracy of 0.3 °,which make it widely used in navigation implements,automobiles,agricultural implements and other fields.Experiment results from high level sprayer showed that compared to the MTi300 AHRS,the average measurement error of roll angle was 0.069 ° and the maximal measurement error was 0.23 ° respectively.The average measurement error of pitch angle was 0.078 ° and the maximal measurement error was 0.39 ° respectively.Test results verified that the proposed Kalman filter algorithm was accuracy and stable,which can improving the quality of agricultural implements operations and have more applicability.
The development of precision agriculture,intelligent agricultural machinery and equipment are an effective way to alleviate the current tense situation in world food security.The complex field environment and meticulous work effects require the agricultural machinery to have the ability to perceive the attitude of the agricultural machinery accurately in real time.For example,the precision navigation control and the leveling control of agricultural implements are all dependent on the accurate measurement of attitude.What's more,the attitude of agricultural implements is one of the key parameters of agricultural mechanics modeling and agricultural implements safety warning learning.However,the external acceleration of the vehicle,which is generally present under dynamic operation conditions,poses a challenge.In order to further improve the precision operation of agricultural machinery and equipment,the paper developed a minimal hardware system for external acceleration identification and attitude estimation used for field working vehicles,and verified by the experiments taken place on the Innova 2100 shaker and the ZP9500 high level sprayer in the field.Modern micro-electromechanical systems(MEMS) technologies provide the moderate-cost and miniaturized solutions for the development of attitude reference system.By using of highly-integrated inertial measurement units(IMUs) ADIS16445 provided by ADI company and micro ARM processor STM32 F446 provided by ST company,the hardware platform was built.ADIS16445 ISensor? included tri-axial gyroscopes and tri-axial accelerometers,the raw sensors data was sampled by STM32 F446 RC processor through SPI interface.The attitude calculation was carried out based on the direction cosine matrix algorithm.Based on the gyroscope and accelerometer measurement model,an one order external acceleration measurement model was proposed,and a Kalman filter fusion algorithm with 4 state vectors was established.Since the bias of gyroscopes and accelerometers was stable after hardware preheated,the impact of bias of MEMS inertial sensors in the fusion algorithm was not considered.Innova 2100 shaker is a standard equipment of rotary motion,by setting different rotation speed,different centripetal accelerations can be achieved to verify the external acceleration identification.Innova 2100 shaker test results showed that the measure error was less than 0.214 m/s2 under the external acceleration lower than 10 g.Field experiments were conducted on Innova 2100 shaker and the ZP9500 high level sprayer provided by LOVOL company with the assistance of attitude and position reference system(AHRS) MTi300 provided by Xsens company.The MTi300 AHRS provide high precision attitude and heading output with high stability and fast dynamic response with dynamic measurement accuracy of 0.3 °,which make it widely used in navigation implements,automobiles,agricultural implements and other fields.Experiment results from high level sprayer showed that compared to the MTi300 AHRS,the average measurement error of roll angle was 0.069 ° and the maximal measurement error was 0.23 ° respectively.The average measurement error of pitch angle was 0.078 ° and the maximal measurement error was 0.39 ° respectively.Test results verified that the proposed Kalman filter algorithm was accuracy and stable,which can improving the quality of agricultural implements operations and have more applicability.
引文
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[9]马超,郑永军,谭彧,等.基于MEMS传感器的两轴姿态调整系统设计与试验[J].农业工程学报,2015,31(增刊1):28-37.Ma Chao,Zheng Yongjun,Tan Yu,et al.Design of two-axis attitude control system based on MEMS sensors[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(Supp.1):28-37.(in Chinese with English abstract)
[10]胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J].农业工程学报,2015,31(10):1-10.Hu Jingtao,Gao Lei,Bai Xiaoping,et al.Review of research on automatic guidance of agricultural vehicles[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(10):1-10.(in Chinese with English abstract)
[11]Ahmed H,Tahir M.Accurate attitude estimation of a moving land vehicle using low-cost MEMS IMU sensors[J].IEEETransactions on Intelligent Transportation Systems,2017,18(7):1723-1739.
[12]Guo Z,Cheng F,Li B,et al.Research development of silicon MEMS gyroscopes:A review[J].Microsystem Technologies,2015,21(10):2053-2066.
[13]华南农业大学.MEMS惯性传感器的车身倾角测量方法:106197376 A[P].2018-08-07.
[14]杨伟伟.水田激光平地机控制系统优化设计[D].广州:华南农业大学,2016.Yang Weiwei.Optimal Design for the Control System for Paddy Field Laser Leveler[D].Guangzhou:South China Agricultural University,2016.(in Chinese with English abstract)
[15]Widodo R B,Wada C.Attitude estimation using kalman filtering:external acceleration compensation considerations[J].Journal of Sensors,2016(10):1-24.
[16]Suh Y S,Park S K,Kang H J,et al.Attitude estimation adaptively compensating external acceleration[J].JSMEInternational Journal Series C Mechanical Systems,Machine Elements and Manufacturing.2006;49(1):172-179.
[17]Guo X,Wang J,Liao F,et al.Distributed adaptive sliding mode control strategy for vehicle-following systems With nonlinear acceleration uncertainties[J].IEEE Transactions on Vehicular Technology,2017,66(2):981-991.
[18]Ligorio G,Sabatini A M.A novel kalman filter for human motion tracking with an inertial-based dynamic inclinometer[J]IEEE Trans Biomed Eng,2015,62(8):2033-2043.
[19]Sabatini A M.Estimating three-dimensional orientation of human body parts by inertial/magnetic sensing[J].Sensors,2011,11(2):1489-1525.
[20]孟唐宇,浦剑涛,方建军,等.姿态解算与外力加速度同步估计算法[J].计算机应用,2016,36(5):1469-1474.Meng Tangyu,Pu Jiantao,Fang Jianjun,et al.Synchronization estimation algorithm for attitude algorithm and external force acceleration[J].Transactions of Journal of Computer Applications,2016,36(5):1469-1474.(in Chinese with English abstract)
[21]Suh Y S.Orientation estimation using a quaternion-based indirect kalman filter with adaptive estimation of external acceleration[J].IEEE Transactions on Instrumentation&Measurement,2010,59(12):3296-3305.
[22]Lee J K,Park E J,Robinovitch S N.Estimation of attitude and external acceleration using inertial sensor measurement during various dynamic conditions[J].IEEE Trans Instrum Meas,2012,61(8):2262-2273.
[23]Wu D.Strapdown INS/GPS integrated navigation using geometric algebra[J].Advances in Applied Clifford Algebras,2013,23(3):767-785.
[24]Fourati H,Belkhiat D E.Multisensor attitude estimation:Hundamental concepts and applications[M].New York:CRC Press,2016.
[25]钱华明,夏全喜,阙兴涛,等.基于Kalman滤波的MEMS陀螺仪滤波算法[J].哈尔滨工程大学学报,2010,31(9):1217-1221.Qian Huaming,Xia Quanxi,Que Xingtao,et al.Algorithm for a MEMS gyroscope based on kalman filter[J].Transactions of Journal of Harbin Engineering University,2010,31(9):1217-1221.(in Chinese with English abstract)
[26]Rados?aw Cechowicz.Bias drift estimation for MEMSgyroscope used in inertial navigation[J].Acta Mechanica Et Automatica,2017,11(2):104-110.
[27]He P,Cardou P,Desbiens A,et al.Estimating the orientation of a rigid body moving in space using inertial sensors[J].Multibody System Dynamics,2015,35(1):63-89.
[28]Welch G.An introduction to the kalman filter[J].Course Notes of Acm Siggraph,1995,8(7):127-132.
[29]STMicroelectronics,STM32F446RC[EB/OL].http://www.st.com/content/st_com/zh/products/microcontroll ers/stm32-32-bit-arm-cortex-mcus/stm32f4-series/stm32f446/stm32f446rc.html.[2018-08-05]
[30]Analog Devices,ADIS16445_cn[EB/OL].https://www.analog.com/en/products/adis16445.html#product-overview.(2018-08-05)[2018-12-14].
[31]Crassidis J L,Markley F L,Cheng Y.Survey of nonlinear attitude estimation methods[J].Journal of Guidance Control&Dynamics,2012,30(1):12-28.
[2]Bai G,Ge Y,Hussain W,et al.A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding[J].Computers&Electronics in Agriculture,2016,128(10):181-192.
[3]United Nations Department of Economic and Social Affairs,Population Division(2017).World Population Prospects:The2017 Revision,Key Findings and Advance Tables[Z].http://www.un.org/en/development/desa/population/ESA/P/WP/248.[2018-06-18]
[4]黄培奎,张智刚,罗锡文,等.农机具姿态倾角测量系统设计与试验[J].农业工程学报,2017,33(22):9-16.Huang Peikui,Zhang Zhigang,Luo Xiwen,et al.Design and test of tilt angle measurement system for agricultural implements[J].Transactions of the Chinese Society of Agricultural Engineering(transactions of the CSAE),2017,33(22):9-16.(in Chinese with English abstract)
[5]罗锡文,廖娟,胡炼,等.提高农业机械化水平促进农业可持续发展[J].农业工程学报,2016,32(1):1-11.Luo Xiwen,Liao Juan,Hu Lian,et al.Improving agricultural mechanization level to promote agricultural sustainable development[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2016,32(1):1-11.(in Chinese with English abstract)
[6]罗锡文,廖娟,邹湘军,等.信息技术提升农业机械化水平[J].农业工程学报,2016,32(20):1-14.Luo Xiwen,Liao Juan,Zou Xiangjun,et al.Enhancing agricultural mechanization level through information technology[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2016,32(20):1-14.(in Chinese with English abstract)
[7]黄培奎,赵祚喜,靳俊栋,等.基于Auto Trac的导航控制参数整定方法试验[J].农业工程学报,2015,31(增刊2):100-106.Huang Peikui,Zhao Zuoxi,Jin Jundong,et al.Navigation control parameter tuning method based on AutoTrac[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(Supp.2):100-106.(in Chinese with English abstract)
[8]胡炼,林潮兴,罗锡文,等.农机具自动调平控制系统设计与试验[J].农业工程学报,2015,31(8):15-20.Hu Lian,Lin Chaoxing,Luo Xiwen,et al.Design and experiment on auto leveling control system of agricultural implements[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(8):15-20.(in Chinese with English abstract)
[9]马超,郑永军,谭彧,等.基于MEMS传感器的两轴姿态调整系统设计与试验[J].农业工程学报,2015,31(增刊1):28-37.Ma Chao,Zheng Yongjun,Tan Yu,et al.Design of two-axis attitude control system based on MEMS sensors[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(Supp.1):28-37.(in Chinese with English abstract)
[10]胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J].农业工程学报,2015,31(10):1-10.Hu Jingtao,Gao Lei,Bai Xiaoping,et al.Review of research on automatic guidance of agricultural vehicles[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(10):1-10.(in Chinese with English abstract)
[11]Ahmed H,Tahir M.Accurate attitude estimation of a moving land vehicle using low-cost MEMS IMU sensors[J].IEEETransactions on Intelligent Transportation Systems,2017,18(7):1723-1739.
[12]Guo Z,Cheng F,Li B,et al.Research development of silicon MEMS gyroscopes:A review[J].Microsystem Technologies,2015,21(10):2053-2066.
[13]华南农业大学.MEMS惯性传感器的车身倾角测量方法:106197376 A[P].2018-08-07.
[14]杨伟伟.水田激光平地机控制系统优化设计[D].广州:华南农业大学,2016.Yang Weiwei.Optimal Design for the Control System for Paddy Field Laser Leveler[D].Guangzhou:South China Agricultural University,2016.(in Chinese with English abstract)
[15]Widodo R B,Wada C.Attitude estimation using kalman filtering:external acceleration compensation considerations[J].Journal of Sensors,2016(10):1-24.
[16]Suh Y S,Park S K,Kang H J,et al.Attitude estimation adaptively compensating external acceleration[J].JSMEInternational Journal Series C Mechanical Systems,Machine Elements and Manufacturing.2006;49(1):172-179.
[17]Guo X,Wang J,Liao F,et al.Distributed adaptive sliding mode control strategy for vehicle-following systems With nonlinear acceleration uncertainties[J].IEEE Transactions on Vehicular Technology,2017,66(2):981-991.
[18]Ligorio G,Sabatini A M.A novel kalman filter for human motion tracking with an inertial-based dynamic inclinometer[J]IEEE Trans Biomed Eng,2015,62(8):2033-2043.
[19]Sabatini A M.Estimating three-dimensional orientation of human body parts by inertial/magnetic sensing[J].Sensors,2011,11(2):1489-1525.
[20]孟唐宇,浦剑涛,方建军,等.姿态解算与外力加速度同步估计算法[J].计算机应用,2016,36(5):1469-1474.Meng Tangyu,Pu Jiantao,Fang Jianjun,et al.Synchronization estimation algorithm for attitude algorithm and external force acceleration[J].Transactions of Journal of Computer Applications,2016,36(5):1469-1474.(in Chinese with English abstract)
[21]Suh Y S.Orientation estimation using a quaternion-based indirect kalman filter with adaptive estimation of external acceleration[J].IEEE Transactions on Instrumentation&Measurement,2010,59(12):3296-3305.
[22]Lee J K,Park E J,Robinovitch S N.Estimation of attitude and external acceleration using inertial sensor measurement during various dynamic conditions[J].IEEE Trans Instrum Meas,2012,61(8):2262-2273.
[23]Wu D.Strapdown INS/GPS integrated navigation using geometric algebra[J].Advances in Applied Clifford Algebras,2013,23(3):767-785.
[24]Fourati H,Belkhiat D E.Multisensor attitude estimation:Hundamental concepts and applications[M].New York:CRC Press,2016.
[25]钱华明,夏全喜,阙兴涛,等.基于Kalman滤波的MEMS陀螺仪滤波算法[J].哈尔滨工程大学学报,2010,31(9):1217-1221.Qian Huaming,Xia Quanxi,Que Xingtao,et al.Algorithm for a MEMS gyroscope based on kalman filter[J].Transactions of Journal of Harbin Engineering University,2010,31(9):1217-1221.(in Chinese with English abstract)
[26]Rados?aw Cechowicz.Bias drift estimation for MEMSgyroscope used in inertial navigation[J].Acta Mechanica Et Automatica,2017,11(2):104-110.
[27]He P,Cardou P,Desbiens A,et al.Estimating the orientation of a rigid body moving in space using inertial sensors[J].Multibody System Dynamics,2015,35(1):63-89.
[28]Welch G.An introduction to the kalman filter[J].Course Notes of Acm Siggraph,1995,8(7):127-132.
[29]STMicroelectronics,STM32F446RC[EB/OL].http://www.st.com/content/st_com/zh/products/microcontroll ers/stm32-32-bit-arm-cortex-mcus/stm32f4-series/stm32f446/stm32f446rc.html.[2018-08-05]
[30]Analog Devices,ADIS16445_cn[EB/OL].https://www.analog.com/en/products/adis16445.html#product-overview.(2018-08-05)[2018-12-14].
[31]Crassidis J L,Markley F L,Cheng Y.Survey of nonlinear attitude estimation methods[J].Journal of Guidance Control&Dynamics,2012,30(1):12-28.