Improved V-SLAM Method for Transmission Line Inspection UAV Based on LightGlue Network

doi:10.3969/j.issn.1006-2475.2025.11.005

Abstract

Abstract: Abstract: To address the problem that the localization accuracy of inspection UAVs is affected by the change of illumination and view angle when they perform visual simultaneous localization and mapping （V-SLAM） in the transmission line environment，an improved Stereo V-SLAM method based on LightGlue network is proposed. Firstly， a SuperPoint feature extraction network is used to extract feature points that are more robust to changes in illumination and viewing angle. Then， the feature matching module is improved by LightGlue network combined with optimized parallel image pyramid model to improve the precision of image feature matching and the real-time performance of algorithm operation. Finally， the point cloud map is converted to an octree map to reduce the memory overhead. The experimental results show that the proposed algorithm is more adaptable to changes in illumination and viewing angle； in the EuRoc dataset test， the localization accuracy is improved by about 28.34% compared with OpenVSLAM， and the real-time performance is improved by 33.30% compared with SL-ORB-SLAM2. In the field experiment， the localization accuracy is improved significantly，and the octree map reduces the memory footprint by about 47.28% compared to the point cloud map. In summary， the algorithm proposed can adapt to the transmission line environment， complete accurate localization in real-time and construct octree maps， which has good engineering application prospect.

Key words: Key words: visual simultaneous localization and mapping, attention mechanism, feature matching, image pyramid

CLC Number:

中图分类号：TP242

ZHU Wenji1, BAN Weihua2, ZOU Lin3, LIU Xu3. Improved V-SLAM Method for Transmission Line Inspection UAV Based on LightGlue Network[J]. Computer and Modernization, 2025, 0(11): 41-48.

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