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Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network

Author

Listed:
  • Dansong Yue

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Shuqi Shang

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Kai Feng

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Haiqing Wang

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
    College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, China)

  • Xiaoning He

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Zelong Zhao

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Ning Zhang

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Baiqiang Zuo

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Dongwei Wang

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

Abstract

Improving the positioning accuracy and stability of a single BDS/INS sensor system in agricultural machinery is important for expanding the application scenarios of agricultural machinery. This paper proposes a navigation and positioning model based on an improved bee-colony-algorithm-optimized BP network (the IABC-BP model). The main aspect of this work involves introducing adaptive coefficients and speed adjustment coefficients that obey Gaussian distribution to ensure the balance between the rate of convergence, group flexibility, and searchability in the search process. The implicit adaptive layer formula of the BP network is proposed, and the BDS/INS navigation and positioning model for agricultural machinery is established using the IABC algorithm and the Kalman filter. Simulation tests and analyses of real-world application scenarios were conducted on the model, and the results showed that, compared with the original model, the performance of the model improved by 90.65%, 84.11%, and 25.96%, indicating that the proposed model has high accuracy and effectiveness. In the information fusion and compensation correction mode, the algorithm processes errors such as longitude and latitude within the target range and can achieve reliable navigation and positioning accuracy in a short period. At the same time, the model has good stability and generalization ability, and can be applied to other navigation scenarios in the future to expand its application scope.

Suggested Citation

  • Dansong Yue & Shuqi Shang & Kai Feng & Haiqing Wang & Xiaoning He & Zelong Zhao & Ning Zhang & Baiqiang Zuo & Dongwei Wang, 2023. "Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network," Agriculture, MDPI, vol. 13(9), pages 1-24, September.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:9:p:1769-:d:1234481
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    References listed on IDEAS

    as
    1. Junjun Tang & Peijuan Li, 2020. "Airborne Integrated Navigation System Based on SINS/GPS/TAN/EOAN," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, November.
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    Cited by:

    1. Fan Yang & Lei Liu & Yanan Zhang & Yuefeng Du & Enrong Mao & Zhongxiang Zhu & Zhen Li, 2024. "Research on a Variable Universe Control Method and the Performance of Large Sprayer Active Suspension Based on an Artificial Fish Swarm Algorithm–Back Propagation Fuzzy Neural Network," Agriculture, MDPI, vol. 14(6), pages 1-26, May.

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