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Relative pose estimation with efficient feature distribution in landing guidance
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作者 Hao Liu Ran Liu +2 位作者 Xiaolei Qu Hui Huang Yu Wang 《Journal of Control and Decision》 2026年第1期103-116,共14页
Relying on vision forfeature keypoint extraction,matching,and Perspective-n-points(PnP)calculation to achieve relative pose estimation is an effective solution forcarrierbased aircraft to achieve high-precision autono... Relying on vision forfeature keypoint extraction,matching,and Perspective-n-points(PnP)calculation to achieve relative pose estimation is an effective solution forcarrierbased aircraft to achieve high-precision autonomous landing.Existingmethods typically only perform global consistency feature detection withoutverifying the reliability of the detected features or considering the featuredistribution of key points.To address this issue,we propose a carrier-basedaircraft landing guidance state estimation algorithm based on efficientdistribution sampling of deep features.By extracting key points with highstate values,the relative pose estimation of the landing process is achieved.A multi-level feature coupling is constructed to establish a variable scale keypoint localization mechanism for key point extraction and detection.Anattention mechanism module is constructed to evaluate the state of highreliability key points.The experimental results show that the proposed methodhas better robustness and relative pose estimation accuracy,achieving robustand high-precision online relative pose measurement in airborne monocularvision landing guidance. 展开更多
关键词 Keypoint extraction non-maximum suppression relative pose estimation landing guidance feature matching
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