Research on Greenhouse Positioning Based on Multi-Source Information Fusion
- 1 Beijing Nanshan Agricultural Ecological Garden Co., Ltd., Beijing, China
Abstract
With the deep penetration of modern technology into the agricultural field, greenhouses have become an indispensable part of agricultural production, and the demand for internal navigation and positioning technology is increasingly prominent. Due to the shielding nature of the internal environment of greenhouses, traditional single navigation positioning methods often fall short in pursuing high-precision positioning. Therefore, this article aims to address the navigation and positioning challenges in greenhouse environments by conducting in-depth research on multi-source information fusion positioning methods to improve positioning accuracy and stability. This article establishes a novel multi-source navigation algorithm. This algorithm integrates data from multiple sensors, including but not limited to GNSS signals, IMU data, and magnetic field information, to achieve more accurate positioning results. To verify the correctness and effectiveness of the proposed algorithm, a navigation and positioning device was designed and extensively tested through experiments. Through the experimental verification of this device, the performance and reliability of the algorithm can be more accurately evaluated. After experimental verification, the multi-source information fusion positioning method adopted in this article demonstrates higher positioning accuracy and stronger robustness in greenhouse environments, providing strong support for precise management of greenhouse agricultural production and effectively responding to complex and changing greenhouse environments. In addition, simulation testing and functional testing have been completed, further confirming the practical application effect of the algorithm. This article not only provides innovative solutions for precise navigation of greenhouses, but also brings new inspiration and methods to the research of positioning technology in related fields, promoting the further development of positioning technology.
- Chen, Q., Xie, Y., Guo, S., Bai, J. and Shu, Q. (2021) Sensing System of Environmental Perception Technologies for Driverless Vehicle: A Review of State of the Art and Challenges. Sensors and Actuators A : Physical , 319, Article ID: 112566. https://doi.org/10.1016/j.sna.2021.112566
- Ma, W.F., Shi, J.Z., Ge, L.H., Dai, K., Zhong, S.R. and Wu, L. (2020) Research Progress on Monocular Visual Odometry for Autonomous Vehicles. Journal of Jilin University ( Engineering and Technology Edition ), 50, 765-775.
- Wu, X.Y. (2018) Research on Pose Estimation of Autonomous Vehicles Based on Laser Odometry. Master’s Thesis, Chang’an University.
- Li, X., Li, Q., Yin, C. and Zhang, J. (2022) Autonomous Navigation Technology for Low-Speed Small Unmanned Vehicle: An Overview. World Electric Vehicle Journal , 13, Article 165. https://doi.org/10.3390/wevj13090165
- Qiao, X., Li, X.M. and Xiao, D.Y. (2019) Indoor Positioning Design Based on Ultrasonic Ranging. Electronic Design Engineering , 27, 102-105.
- Li, B.X., Qi, H.R., Lu, Y. and Tang, Y. (2020) Overview of Indoor Positioning Algorithms and Technologies. Electronic Components and Information Technology , 4, 47-50.
- Babak, E.S., Mahdi, R.,Rodolfo, V., Arash, R. and Yaser, P.F. (2022) High-Definition Map Representation Techniques for Automated Vehicles. Electronics , 11, Article 3374. https://doi.org/10.3390/electronics11203374
- Peng, Y.S., Li, J.L., Xu, Z.F., He, G.H. and Jia, P. (2021) Overview and Prospect of Blue-Tooth Indoor Positioning Technology. Household Appliances , No. 12, 58-64.
- Ge, M.J. and Zhao, Z.H. (2021) Indoor Positioning System for the Internet of Things Based on Bluetooth Technology. The Internet of Things , 11, 52-57.
- Mair, N. and Mahmoud, Q. (2012) A Collaborative Bluetooth-Based Approach to Localization of Mobile Devices. Proceedings of the 8 th IEEE International Conference on Colla borative Computing : Networking , Applications and Worksharing , Pittsburgh, 14-17 October 2012, 1-9. https://doi.org/10.4108/icst.collaboratecom.2012.250437
- Wang, W. and Zhu, Q.S. (2021) Research on Circular Triangle Localization Algorithm in Wireless Sensor Networks. Modern Electronic Technology , 44, 47-50.
- Zhang, J. and Chen, W.L. (2021) Research on Indoor Personnel Positioning System Based on ZigBee Node Technology. Scientific and Technological Innovation , No. 20, 173-174.