A seamless LiDAR/IMU/RTK fused localization method for UAV-Based bridge inspection

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Udgivet i:The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences vol. XLVIII-G-2025 (2025), p. 937
Hovedforfatter: Liang, Anbang
Andre forfattere: Pan, Yirong, Huo, Yuelong, Li, Qingquan, Zhou, Baoding, Chen, Zhipeng
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Copernicus GmbH
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100 1 |a Liang, Anbang  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
245 1 |a A seamless LiDAR/IMU/RTK fused localization method for UAV-Based bridge inspection 
260 |b Copernicus GmbH  |c 2025 
513 |a Journal Article 
520 3 |a The Simultaneous Localization and Mapping (SLAM) technology is fundamental to the autonomous navigation of Unmanned Aerial Vehicles (UAVs) and holds significant value for the realization of UAV-based bridge inspections. However, conventional SLAM methods for UAV face challenges related to low continuity and weak reliability across different scenes, making it difficult to meet the requirements for comprehensive bridge localization and mapping. To address the limitations of existing UAV-based SLAM approaches, we propose a seamless SLAM system that integrates IMU, LiDAR, and RTK. In open scenes (such as the top and sides of a bridge), high-precision absolute localization is achieved by fusing IMU and RTK through an iterative error-state Kalman filter (IESKF). In occluded environments (such as the underside of a bridge), an IMU/LiDAR odometry is used to recursively estimate the UAV’s pose. In cross-scene situations (when the UAV passes through a bridge arch), the quality of sensor data is evaluated based on an interactive multi-model (IMM), and an adaptive switching mechanism is employed between two localization modes—IMU/RTK mode and IMU/LiDAR mode—ensuring smooth and seamless multi-source fusion localization even in the presence of sensor signal fluctuations. To validate the effectiveness of our method, extensive tests were conducted on several real-world bridge scenarios. The results show that our method can achieve centimetre-level cross-scene localization accuracy in bridge inspection applications, which indicates its feasibility and effectiveness. 
653 |a Localization method 
653 |a Mapping 
653 |a Simultaneous localization and mapping 
653 |a Arch bridges 
653 |a Inspection 
653 |a Unmanned aerial vehicles 
653 |a Navigation 
653 |a Effectiveness 
653 |a Lidar 
653 |a Autonomous navigation 
653 |a Localization 
653 |a Bridge inspection 
653 |a Kalman filters 
653 |a Economic 
700 1 |a Pan, Yirong  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
700 1 |a Huo, Yuelong  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
700 1 |a Li, Qingquan  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
700 1 |a Zhou, Baoding  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
700 1 |a Chen, Zhipeng  |u School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China; School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China 
773 0 |t The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences  |g vol. XLVIII-G-2025 (2025), p. 937 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3234309537/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3234309537/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch