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Heading Estimation for Agricultural Vehicles with Multi-antenna RTK/GNSS, Tactical-Grade and Low-Cost MEMS IMUs

Yıl 2025, Cilt: 11 Sayı: 1, 153 - 166, 30.04.2025

Hasan Dilmaç , Veli İlçi , Emirhan Kaya

Öz

Nowadays, autonomous vehicles (AVs) are employed for a wide range of jobs, including spraying, harvesting, and planting. For AVs to navigate autonomously, accurate heading knowledge of the vehicle is essential. Sensors such as the global navigation satellite system (GNSS) and inertial measurement unit (IMU) are used on AVs to produce heading information. Dual-frequency and RTK-capable systems with multiple antennas are used to increase the heading accuracy of GNSS. For IMUs, heading accuracy is directly related to the quality of the sensors, so high accuracy is achieved with expensive IMUs. However, with the development of micro-electro-mechanical system (MEMS) technology, studies are also being carried out on low-cost IMU solutions. In this study, the heading performances of three different sensors, a low-cost RTK/GNSS with multiple antennas, a tactical-grade IMU, and a low-cost MEMS IMU, were tested. An unmanned ground agricultural vehicle (UGAV) designed for spraying was driven on a line, and the data of the sensors mounted on the UGAV were collected. Heading accuracy was also examined according to the distance between the antennas of the RTK/GNSS system. As a result of the analysis, the average errors of RTK/GNSS, tactical-grade IMU, and low-cost IMU are 0.58, 0.60, and 4.24 degrees, respectively.

Anahtar Kelimeler

Autonomous vehicles heading GNSS IMU

Etik Beyan

The manuscript or any parts of the manuscript have not been published and are not submitted elsewhere while in the review process for the journal.

Destekleyen Kurum

Ondokuz Mayıs University

Proje Numarası

This work was supported by the Ondokuz Mayis University under Grant PYO.MUH.1908.22.078

Kaynakça

  • [1] D. T. Fasiolo, L. Scalera, E. Maset, and A. Gasparetto, “Towards autonomous mapping in agriculture: A review of supportive technologies for ground robotics,” Rob Auton Syst, vol. 169, Nov. 2023. doi: 10.1016/j.robot.2023.104514
  • [2] K. R. Aravind, P. Raja, and M. Pérez-Ruiz, “Task-based agricultural mobile robots in arable farming: A review,” Spanish Journal of Agricultural Research, vol. 15, no. 1, 2017. doi: 10.5424/sjar/2017151-9573
  • [3] A. Ghobadpour, G. Monsalve, A. Cardenas, and H. Mousazadeh, “Off-Road Electric Vehicles and Autonomous Robots in Agricultural Sector: Trends, Challenges, and Opportunities,” Vehicles, vol. 4, no. 3, pp. 843-864, 2022. doi: 10.3390/vehicles4030047
  • [4] M. Nørremark, H. W. Griepentrog, J. Nielsen, and H. T. Søgaard, “The development and assessment of the accuracy of an autonomous GPS-based system for intra-row mechanical weed control in row crops,” Biosystems Engineering, vol. 101, no. 4, pp. 396–410, 2008. doi: 10.1016/j.biosystemseng.2008.09.007
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  • [29] F. Zhu, Z. Hu, W. Liu, and X. Zhang, “Dual-Antenna GNSS Integrated with MEMS for Reliable and Continuous Attitude Determination in Challenged Environments,” IEEE Sensors Journal, vol. 19, no. 9, pp. 3449–3461, May 2019. doi: 10.1109/JSEN.2019.2891783
  • [30] J. Y. Huang, Z. Y. Huang, and K. H. Chen, “Combining Low-Cost Inertial Measurement Unit (IMU) and Deep Learning Algorithm for Predicting Vehicle Attitude,” in IEEE Conference on Dependable and Secure Computing, Taipei, Taiwan, October 7-10, 2017, IEEE, pp. 237–239. doi: 10.1109/DESEC.2017.8073847
  • [31] A. H. Işık and Ö. Çetin, “Multifunctional and Low Cost Autonomous Mobile Robot,” Gazi Journal of Engineering Sciences, vol. 6, no. 2, pp. 105–110, Aug. 2020. doi: 10.30855/gmbd.2020.02.02
  • [32] ArduSimple, “SimpleRTK2B SBC - Development Kit.” Accessed: May 28, 2024. [Online]. Available: https://www.ardusimple.com/product/simplertk2b-sbc-development-kit/
  • [33] S. Ji, R. Du, W. Chen, Z. Wang, K. He, and Z. Nie, “Partial GNSS ambiguity resolution in coordinate domain,” Survey Review, vol. 51, no. 369, pp. 525–532, Nov. 2019. doi: 10.1080/00396265.2018.1490870
  • [34] u-blox, “ZED-F9P Moving base applications Application note: ZED-F9P-MovingBase_AppNote_UBX-19009093,” 2023. [Online]. Available: www.u-blox.com
  • [35] J. Keong and G. Lachapelle, “Heading and Pitch Determination Using GPS/GLONASS,” GPS Solutions, vol. 3, pp. 26-36, 2000. Available: https://doi.org/10.1007/PL00012800
  • [36] Xsens, “Xsens MTi 630.” Accessed: May 28, 2024. [Online]. Available: https://www.movella.com/products/sensor-modules/xsens-mti-630-ahrs
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  • [38] X. Cui, Y. Li, Q. Wang, M. Karaim, and A. Noureldin, “Vehicle heading estimation of INS/magnetometer integrated system based on constant hard iron interference calibration,” Measurement and Control, vol. 54, no. 7–8, pp. 1208–1218, Sep. 2021, doi: 10.1177/00202940211021876
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Yıl 2025, Cilt: 11 Sayı: 1, 153 - 166, 30.04.2025

Hasan Dilmaç , Veli İlçi , Emirhan Kaya

Öz

Proje Numarası

This work was supported by the Ondokuz Mayis University under Grant PYO.MUH.1908.22.078

Kaynakça

  • [1] D. T. Fasiolo, L. Scalera, E. Maset, and A. Gasparetto, “Towards autonomous mapping in agriculture: A review of supportive technologies for ground robotics,” Rob Auton Syst, vol. 169, Nov. 2023. doi: 10.1016/j.robot.2023.104514
  • [2] K. R. Aravind, P. Raja, and M. Pérez-Ruiz, “Task-based agricultural mobile robots in arable farming: A review,” Spanish Journal of Agricultural Research, vol. 15, no. 1, 2017. doi: 10.5424/sjar/2017151-9573
  • [3] A. Ghobadpour, G. Monsalve, A. Cardenas, and H. Mousazadeh, “Off-Road Electric Vehicles and Autonomous Robots in Agricultural Sector: Trends, Challenges, and Opportunities,” Vehicles, vol. 4, no. 3, pp. 843-864, 2022. doi: 10.3390/vehicles4030047
  • [4] M. Nørremark, H. W. Griepentrog, J. Nielsen, and H. T. Søgaard, “The development and assessment of the accuracy of an autonomous GPS-based system for intra-row mechanical weed control in row crops,” Biosystems Engineering, vol. 101, no. 4, pp. 396–410, 2008. doi: 10.1016/j.biosystemseng.2008.09.007
  • [5] A. T. Meshram, A. V. Vanalkar, K. B. Kalambe, and A. M. Badar, “Pesticide spraying robot for precision agriculture: A categorical literature review and future trends,” Journal of Field Robotics, vol. 39, no. 2, pp. 153–171, 2022. doi: 10.1002/rob.22043
  • [6] W. Ji, D. Zhao, F. Cheng, B. Xu, Y. Zhang, and J. Wang, “Automatic recognition vision system guided for apple harvesting robot,” Computers and Electrical Engineering, vol. 38, no. 5, pp. 1186–1195, 2012. doi: 10.1016/j.compeleceng.2011.11.005
  • [7] Y. Zhao, L. Gong, C. Liu, and Y. Huang, “Dual-arm Robot Design and Testing for Harvesting Tomato in Greenhouse,” IFAC-PapersOnLine, vol. 49, no. 16, pp. 161–165, 2016. doi: 10.1016/j.ifacol.2016.10.030
  • [8] H. Zhou, X. Wang, W. Au, H. Kang, and C. Chen, “Intelligent robots for fruit harvesting: recent developments and future challenges,” Precision Agriculture, vol. 23, pp. 1856-1907, 2022. doi: 10.1007/s11119-022-09913-3
  • [9] P. Gonzalez-de-Santos, A. Ribeiro, C. Fernandez-Quintanilla, et al., “Fleets of robots for environmentally-safe pest control in agriculture,” Precision Agriculture, vol. 18, no. 4, pp. 574–614, 2017. doi: 10.1007/s11119-016-9476-3
  • [10] T. L. Oluwabunmi, O. Adenugba, I. A. Ayoade, J. Azeta, and C. A. Bolu, “Development of an Autonomous Vehicle for Smart Irrigation,” in 2022 5th Information Technology for Education and Development (ITED), Abuja, Nigeria, November 1-3, 2022, IEEE, pp. 1-7. doi: 10.1109/ITED56637.2022.10051388
  • [11] A. Bechar and C. Vigneault, “Agricultural robots for field operations. Part 2: Operations and systems,” Biosystems Engineering, vol. 153, pp. 110–128, 2017. doi: 10.1016/j.biosystemseng.2016.11.004
  • [12] Y. Bai, B. Zhang, N. Xu, J. Zhou, J. Shi, and Z. Diao, “Vision-based navigation and guidance for agricultural autonomous vehicles and robots: A review,” Computers and Electronics in Agriculture, vol. 205, no. 107584, 2023. doi: 10.1016/j.compag.2022.107584
  • [13] T. Bakker, K. van Asselt, J. Bontsema, J. Müller, and G. van Straten, “Autonomous navigation using a robot platform in a sugar beet field,” Biosystems Engineering, vol. 109, no. 4, pp. 357–368, 2011. doi: 10.1016/j.biosystemseng.2011.05.001
  • [14] X. Han, H. J. Kim, C. W. Jeon, H. C. Moon, J. H. Kim, and S. Y. Yi, “Application of a 3D tractor-driving simulator for slip estimation-based path-tracking control of auto-guided tillage operation,” Biosystems Engineering, vol. 178, pp. 70–85, 2019. doi: 10.1016/j.biosystemseng.2018.11.003
  • [15] S. Alonso-Garcia, J. Gomez-Gil, and J. I. Arribas, “Evaluation of the use of low-cost GPS receivers in the autonomous guidance of agricultural tractors,” Spanish Journal of Agricultural Research, vol. 9, no. 2, pp. 378–388, 2011. [Online]. Available: www.inia.es/sjar
  • [16] J. H. Han, C. H. Park, Y. J. Park, and J. H. Kwon, “Preliminary results of the development of a single-frequency GNSS RTK-based autonomous driving system for a speed sprayer,” Journal of Sensors, vol. 2019, no. 1, 2019. doi: 10.1155/2019/4687819
  • [17] A. Leanza, R. Galati, A. Ugenti, E. Cavallo, and G. Reina, “Where am I heading? A robust approach for orientation estimation of autonomous agricultural robots,” Computers and Electronics in Agriculture, vol. 210, Jul. 2023. doi: 10.1016/j.compag.2023.107888
  • [18] A. Mizushima, K. Ishii, N. Noguchi, Y. Matsuo, and R. Lu, “Development of a low-cost attitude sensor for agricultural vehicles,” Computers and Electronics in Agriculture, vol. 76, no. 2, pp. 198–204, May 2011. doi: 10.1016/j.compag.2011.01.017
  • [19] D. Jiang, L. Yang, D. Li, F. Gao, L. Tian, and L. Li, “Development of a 3D ego-motion estimation system for an autonomous agricultural vehicle,” Biosystems Engineering, vol. 121, pp. 150–159, 2014. doi: 10.1016/j.biosystemseng.2014.02.016
  • [20] A. Roshanianfard, N. Noguchi, H. Okamoto, and K. Ishii, “A review of autonomous agricultural vehicles (The experience of Hokkaido University),” Journal of Terramechanics, vol. 91, pp. 155-183, October 2020. doi: 10.1016/j.jterra.2020.06.006
  • [21] S. Sasani, J. Asgari, and A. R. Amiri-Simkooei, “Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications,” GPS Solutions, vol. 20, no. 1, pp. 89–100, Jan. 2016. doi: 10.1007/s10291-015-0471-3
  • [22] Y. Li, M. Efatmaneshnik, and A. G. Dempster, “Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications,” GPS Solutions, vol. 16, no. 1, pp. 41–52, Jan. 2012. doi: 10.1007/s10291-011-0207-y
  • [23] L. Cong, E. Li, H. Qin, K. V. Ling, and R. Xue, “A performance improvement method for low-cost land vehicle GPS/MEMS-INS attitude determination,” Sensors, vol. 15, no. 3, pp. 5722–5746, Mar. 2015. doi: 10.3390/s150305722
  • [24] J. Si, Y. Niu, J. Lu, and H. Zhang, “High-Precision Estimation of Steering Angle of Agricultural Tractors Using GPS and Low-Accuracy MEMS,” IEEE Transactions on Vehicular Technology, vol. 68, no. 12, pp. 11738–11745, Dec. 2019. doi: 10.1109/TVT.2019.2949298
  • [25] J. H. Han, C. H. Park, Y. Y. Jang, J. D. Gu, and C. Y. Kim, “Performance evaluation of an autonomously driven agricultural vehicle in an orchard environment,” Sensors, vol. 22, no. 1, Jan. 2022. doi: 10.3390/s22010114
  • [26] J. Jackson, R. Saborio, S. A. Ghazanfar, D. Gebre-Egziabher, and B. Davis, “Evaluation of Low-Cost, Centimeter-Level Accuracy OEM GNSS Receivers,” the University Digital Conservancy, 2018. Available: https://hdl.handle.net/11299/197453.2018
  • [27] M. Farkas, S. Rózsa, and B. Vanek, “Multi-sensor Attitude Estimation using Quaternion Constrained GNSS Ambiguity Resolution and Dynamics-Based Observation Synchronization,” Acta Geodaetica et Geophysica, vol. 59, pp. 51-71, Mar. 2024. doi: 10.1007/s40328-024-00441-2
  • [28] N. Nadarajah, P. J. G. Teunissen, and N. Raziq, “Instantaneous GPS-galileo attitude determination: Single-frequency performance in satellite-deprived environments,” IEEE Transactions on Vehicular Technology, vol. 62, no. 7, pp. 2963–2976, 2013. doi: 10.1109/TVT.2013.2256153
  • [29] F. Zhu, Z. Hu, W. Liu, and X. Zhang, “Dual-Antenna GNSS Integrated with MEMS for Reliable and Continuous Attitude Determination in Challenged Environments,” IEEE Sensors Journal, vol. 19, no. 9, pp. 3449–3461, May 2019. doi: 10.1109/JSEN.2019.2891783
  • [30] J. Y. Huang, Z. Y. Huang, and K. H. Chen, “Combining Low-Cost Inertial Measurement Unit (IMU) and Deep Learning Algorithm for Predicting Vehicle Attitude,” in IEEE Conference on Dependable and Secure Computing, Taipei, Taiwan, October 7-10, 2017, IEEE, pp. 237–239. doi: 10.1109/DESEC.2017.8073847
  • [31] A. H. Işık and Ö. Çetin, “Multifunctional and Low Cost Autonomous Mobile Robot,” Gazi Journal of Engineering Sciences, vol. 6, no. 2, pp. 105–110, Aug. 2020. doi: 10.30855/gmbd.2020.02.02
  • [32] ArduSimple, “SimpleRTK2B SBC - Development Kit.” Accessed: May 28, 2024. [Online]. Available: https://www.ardusimple.com/product/simplertk2b-sbc-development-kit/
  • [33] S. Ji, R. Du, W. Chen, Z. Wang, K. He, and Z. Nie, “Partial GNSS ambiguity resolution in coordinate domain,” Survey Review, vol. 51, no. 369, pp. 525–532, Nov. 2019. doi: 10.1080/00396265.2018.1490870
  • [34] u-blox, “ZED-F9P Moving base applications Application note: ZED-F9P-MovingBase_AppNote_UBX-19009093,” 2023. [Online]. Available: www.u-blox.com
  • [35] J. Keong and G. Lachapelle, “Heading and Pitch Determination Using GPS/GLONASS,” GPS Solutions, vol. 3, pp. 26-36, 2000. Available: https://doi.org/10.1007/PL00012800
  • [36] Xsens, “Xsens MTi 630.” Accessed: May 28, 2024. [Online]. Available: https://www.movella.com/products/sensor-modules/xsens-mti-630-ahrs
  • [37] Adafruit, “BNO055 Intelligent 9-axis absolute orientation sensor,” 2016. [Online]. Available: https://www.bosch-sensortec.com/products/smart-sensor-systems/bno055/
  • [38] X. Cui, Y. Li, Q. Wang, M. Karaim, and A. Noureldin, “Vehicle heading estimation of INS/magnetometer integrated system based on constant hard iron interference calibration,” Measurement and Control, vol. 54, no. 7–8, pp. 1208–1218, Sep. 2021, doi: 10.1177/00202940211021876
  • [39] P. Kaniewski and J. Kazubek, “Integrated System for Heading Determination,” Acta Physica Polonica A, vol. 116, no. 3, pp. 325-330, 2009.
  • [40] B. Li, T. Gallagher, A. G. Dempster, and C. Rizos, “How feasible is the use of magnetic field alone for indoor positioning?” in 2012 International Conference on Indoor Positioning and Indoor Navigation, Sydney, NSW, Australia, November 13-15, 2012, IEEE, pp. 1-9. doi: 10.1109/IPIN.2012.6418880
  • [41] USGS, “What do the different north arrows on a USGS topographic map mean?” Accessed: May 29, 2024. [Online]. Available: https://www.usgs.gov/faqs/what-do-different-north-arrows-usgs-topographic-map-mean
  • [42] A. Stoll and H. D. Kutzbach, “Guidance of a Forage Harvester with GPS,” Precision Agriculture, vol. 2, pp. 281–291, 2000.
  • [43] J. Carballido, M. Perez-Ruiz, L. Emmi, and J. Agüera, “Comparison of Positional Accuracy between RTK and RTX GNSS based on The Autonomous Agricultural Vehicles under Field Conditions,” Applied Engineering in Agriculture, vol. 30, no. 3, pp. 361–366, 2014. doi: 10.13031/aea.30.10342
  • [44] B. Cui, J. Zhang, X. Wei, X. Cui, Z. Sun, Y. Zhao, and Y. Liu, “Improved Information Fusion for Agricultural Machinery Navigation Based on Context-Constrained Kalman Filter and Dual-Antenna RTK,” Actuators, vol. 13, no. 5, 2024. doi: 10.3390/act13050160
  • [45] Q, Chen, H. Lin, J. Kuang, Y. Luo, and X. Niu, “Rapid Initial Heading Alignment for MEMS Land Vehicular GNSS/INS Navigation System,” IEEE Sensors Journal, vol. 23, no. 7, pp. 7656–7666, 2023. doi: 10.1109/JSEN.2023.3247587
  • [46] R. Galati, G. Mantriota, and G. Reina, “RoboNav: An Affordable Yet Highly Accurate Navigation System for Autonomous Agricultural Robots,” Robotics, vol. 11, no. 5, 2022. doi: 10.3390/robotics11050099
  • [47] Y. Huang, J. Fu, S. Xu, T. Han, and Y. Liu, “Research on Integrated Navigation System of Agricultural Machinery Based on RTK-BDS/INS,” Agriculture, vol. 12, no. 8, 2022. doi: 10.3390/agriculture12081169
  • [48] M. Pini, G. Marucco, G. Falco, M. Nicola, and W. De Wilde, “Experimental Testbed and Methodology for the Assessment of RTK GNSS Receivers Used in Precision Agriculture,” IEEE Access, vol. 8, pp. 14690–14703, 2020. doi: 10.1109/ACCESS.2020.2965741
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ulaştırma Mühendisliği, İnşaat Mühendisliği (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Hasan Dilmaç 0000-0001-6877-8730

Veli İlçi 0000-0002-9485-874X

Emirhan Kaya 0009-0007-2633-3419

Proje Numarası This work was supported by the Ondokuz Mayis University under Grant PYO.MUH.1908.22.078
Yayımlanma Tarihi 30 Nisan 2025
Gönderilme Tarihi 28 Ocak 2025
Kabul Tarihi 13 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 11 Sayı: 1

Kaynak Göster

IEEE H. Dilmaç, V. İlçi, ve E. Kaya, “Heading Estimation for Agricultural Vehicles with Multi-antenna RTK/GNSS, Tactical-Grade and Low-Cost MEMS IMUs”, GJES, c. 11, sy. 1, ss. 153–166, 2025.
 Kapak Resmi İndir

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