基于因子图的无人机视觉定位方法

doi:10.7527/S1000-6893.2022.27627

Abstract

Abstract:

At present， multi-purpose UAVs mainly rely on the combined navigation of Global Navigation Satellite System（GNSS） and Inertial Measurement Unit（IMU） to achieve high-precision positioning. However， in the cases of strong electromagnetic interference and GNSS rejection in various complex environments， this positioning mode faces the risk of failure. To explore a navigation and positioning method in the GNSS rejection environment，the visual navigation method is studied. To solve the problems of poor intersection accuracy in the elevation direction， lack of absolute scale information， inability to eliminate accumulated errors， and discontinuous positioning trajectory in visual positioning under the condition of small intersection angle of UAV， a bundle adjustment method based on factor graph fusion image matching and visual information is proposed. The problem of autonomous absolute positioning under the small intersection angle of UAV is solved.

Key words: factor graph, bundle adjustment, UAV, visual positioning, image matching

CLC Number:

V249.32⁺9

Hongfa WAN, Shanshan LI, Chaozhen LAN, Mingzhi XIANG. UAV visual positioning method based on factor graph[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S1): 727627-727627.

Figures/Tables 10

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References 25

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实验	组别	RMSE/m	mean/m	std	定位时间/s
实验1	基准影像匹配	20.5	18.4	9.1	312
	视觉里程计	43.8	58.2	26.1	245
	本文算法	6.3	5.9	2.2	266
实验2	基准影像匹配	9.9	8.5	4.9	239
	视觉里程计	15.7	16.3	10.3	215
	本文算法	6.0	4.8	1.6	240
实验3	基准影像匹配	4.1	3.9	1.5	239
	视觉里程计	3.7	3.5	1.3	215
	本文算法	2.7	2.6	0.4	240

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UAV visual positioning method based on factor graph

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