Journal of Astronautics ›› 2022, Vol. 43 ›› Issue (1): 122-130.doi: 10.3873/j.issn.1000-1328.2022.01.014

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Relative Positioning Algorithm of UAV Formation Based on Binocular Vision

ZHOU Wen ya, LI Zhe, XU Yong, YANG Feng, JIA Tao   

  1. 1. School of Aeronautics and Astronautics, Dalian University of Technology, Dalian 116024, China;2. Aerospace Technology Research Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China
  • Received:2021-03-08 Revised:2021-06-04 Online:2022-01-15 Published:2022-01-15

Abstract: Aiming at the technical situation of poor accuracy of binocular vision positioning, large amount of calculation, and low real time performance during UAV formation flying, the oriented fast and rotated brief (ORB) algorithm based on feature points is improved, and an algorithm suitable for binocular vision positioning of UAVs is proposed. In the improved ORB algorithm, the methods of extracting the target area, nearest neighbor constraint and random sampling consensus (RANSAC) are adopted to improve the efficiency of feature point extraction and matching, and also improve the quality of feature point matching. For binocular vision positioning, a binocular vision positioning model with broader applicable conditions is proposed, and the positioning accuracy of the model is guaranteed. Finally, the Kalman filter algorithm is used to estimate the positioning information of the UAV, which further improves the positioning accuracy of the UAV. The experiments show that the algorithm has high accuracy and real time performance, and meets the relative positioning requirements between UAVs.

Key words: Improved ORB algorithm, Binocular visual positioning, Kalman filter, UAV formation

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