Bridge detection unmanned aerial vehicle visual navigation method based on label assistance
A bridge detection and visual navigation technology, applied in surveying and navigation, bridges, navigation and other directions, can solve the problems of high algorithm complexity and large resource occupation, and achieve the effect of improving accuracy, reducing workload and improving positioning accuracy.
Active Publication Date: 2021-09-17
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology
[0004] VIO research is relatively mature, but the algorithm framework includes Kalman filter, pre-integration, Gauss-Newton method, etc., resulting in high algorithm complexity and large resource occupation
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[0039] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0040] The embodiment of the present invention discloses a tag-assisted bridge detection UAV visual navigation method, such as figure 1 shown, including the following steps:
[0041] Step S10, along the flight route of the UAV, arranging a plurality of positioning two-dimensional code labels at intervals on the bridge to be detected; Step S20, during the flight of the UAV, continuously observe the surface of the bridge to be detected through the camera on the UAV, When the camera observes the positioning two-dimensional code label, query the corresponding coordinate value combination according to the positioning two-dimensional code label; step S30, determine the first conversion relationship matrix between the positioning two-dimensional code label and the camera according to the coordinate value combination; step S40 , Combining the first ...
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Abstract
The invention discloses a bridge detection unmanned aerial vehicle visual navigation method based on label assistance, and the method comprises the steps: laying a plurality of positioning two-dimensional code labels on a to-be-detected bridge at intervals along a flight route of an unmanned aerial vehicle; in the flight process of the unmanned aerial vehicle, continuously observing the surface of the to-be-detected bridge through a camera on the unmanned aerial vehicle, and when the camera observes the positioning two-dimensional code label, querying a corresponding coordinate value combination according to the positioning two-dimensional code label; determining a first conversion relation matrix between the positioning two-dimensional code label and the camera according to the coordinate value combination; combining the first conversion relation matrix, the second conversion relation matrix and the coordinate value combination to solve the first position information of the unmanned aerial vehicle; using the first position information to replace the second position information of the unmanned aerial vehicle obtained through the VIO, and continuing the navigation of the unmanned aerial vehicle; according to the method, drift errors generated by a VIO algorithm can be eliminated, the positioning precision is improved, and the workload of back-end optimization is reduced.
Description
technical field [0001] The invention belongs to the technical field of long-span bridge detection, in particular to a tag-assisted visual navigation method for bridge detection drones. Background technique [0002] With the reform and opening up and the rapid development of the national economy, the number of bridges in our country has increased dramatically, and the safety inspection of bridges has become an issue that must be considered. When manual detection methods are applied to high-altitude, deep-water, wide-width, and complex-structured bridges, they face prominent engineering problems such as difficult detection, low efficiency, large blind spots, and safety. The difficulty of bridge detection lies in the detection of unreachable areas under the bridge. . Therefore, the current promising method is to use drones for bridge inspection. [0003] At present, the navigation technology adopted by most drones is GPS satellite navigation, inertial navigation or integrated...
Claims
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Login to View More IPC IPC(8): E01D19/10G01C21/16B64C39/02G06K19/06
CPCE01D19/10G01C21/165B64C39/024G06K19/06037B64U10/10
Inventor 张夷斋杨奇磊黄攀峰张帆刘正雄
Owner NORTHWESTERN POLYTECHNICAL UNIV