AUTHOR=Xue Bayang , Yang Zhong , Liao Luwei , Zhang Chi , Xu Hao , Zhang Qiuyan TITLE=High precision visual localization method of UAV based on feature matching JOURNAL=Frontiers in Computational Neuroscience VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2022.1037623 DOI=10.3389/fncom.2022.1037623 ISSN=1662-5188 ABSTRACT=

In this paper, the precision hovering problem of UAV operation is studied. Aiming at the diversity and complexity of the UAV operating environment, a high-precision visual positioning and orientation method based on image feature matching was proposed. The image feature matching based on the improved AKAZE algorithm is realized, and the optimal matching point pair screening method based on the fusion of Hamming distance and matching line angle is innovatively proposed, which greatly improves the robustness of the algorithm without affecting the performance of the algorithm. The real-time image is matched with the benchmark image for image feature matching. By reducing the deviation of image feature, the pose state correction of UAV hovering is achieved, and the precision hovering of the UAV is realized. Both simulation and real UAV tests verify the effectiveness of the proposed UAV high-precision visual positioning and orientation method.