Abstract
High precision continuous localization is a fundamental challenge for automated guided vehicles (AGVs) operating in electromagnetically sensitive industrial environments. To mitigate the continuity limitations of conventional discrete localization methods and the accuracy limitations of existing continuous localization methods, this paper proposes a continuous AGV localization method that integrates interferometric fiber Bragg grating (FBG) array sensing with a hybrid deep learning framework. We first design a shallowly buried interferometric FBG array sensing track to enable the stable acquisition of high-quality signals. The received sensing signals are subsequently parameterized and preprocessed in a task-oriented manner, in which a multichannel joint representation is constructed using a sliding time window. A hybrid deep learning framework is developed to estimate AGV position from multichannel FBG response signals by jointly exploiting inter-channel spatial correlation and temporal continuity in the measurement sequence. Experimental results show that the proposed method achieves a mean absolute error (MAE) of less than 2 cm under complex industrial conditions, proving its effectiveness and robustness in practical AGV localization scenarios.
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Publication details
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Cite this article
APA 7
Wu, L., Gui, X., Cao, H., Zhang, Y., Wang, H., Wang, J., & Li, Z. (2026). A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning. https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning
MLA 9
Wu, Laiming, et al. "A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning." https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning.
Chicago (author–date)
Wu, Laiming, Xin Gui, Hui Cao, Yunchuan Zhang, Haiyang Wang, Jiaqi Wang, and Zhengying Li. 2026. "A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning." https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning.
Harvard
Wu, L., Gui, X., Cao, H., Zhang, Y., Wang, H., Wang, J. and Li, Z. (2026) 'A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning', Available at: https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning.
Vancouver
Wu L, Gui X, Cao H, Zhang Y, Wang H, Wang J, et al. A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning. https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning
IEEE
L. Wu, X. Gui, H. Cao, Y. Zhang, H. Wang, J. Wang, and Z. Li, "A Continuous High Precision Localization Method for AGVs Based on Interferometric FBG Array Sensing and Hybrid Deep Learning," https://omanscience.com/en/articles/a-continuous-high-precision-localization-method-for-agvs-based-on-interferometric-fbg-array-sensing-and-hybrid-deep-learning.