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Vector constraint-based random characteristic point selection method for landing position detection

A technology of random features and feature points, applied in the field of visual navigation, which can solve the problems that geographic coordinates cannot be calibrated in advance and the number of feature points is large.

Inactive Publication Date: 2016-11-09
XIAN UNIV OF SCI & TECH
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Problems solved by technology

[0003] Compared with the relative pose estimation in the known landing area, there are two main problems in the relative pose parameter estimation of the UAV in the unknown landing area: one is the geographic coordinates of the feature points used to solve the pose equation It is impossible to calibrate in advance, so how to calibrate the geographic coordinates of the feature points online is a difficult problem; second, the number of feature points extracted in the unknown landing area is large and random, and how to select the feature points for pose estimation to make the pose estimation accuracy high, Good real-time performance is also a problem

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  • Vector constraint-based random characteristic point selection method for landing position detection
  • Vector constraint-based random characteristic point selection method for landing position detection

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Embodiment Construction

[0089] Such as figure 1 A random feature point selection method for landing position detection based on vector constraints is shown, including the following steps:

[0090] Step 1. Image acquisition and synchronous upload of the landing area: use image acquisition equipment and follow the pre-designed sampling frequency f 0 Acquiring the image of the landing area, and synchronously transmitting the acquired image of the landing area to the processor for processing; the image acquisition device is connected to the processor; wherein, f 0 ≤30Hz;

[0091] Step 2, landing area image processing: using the processor to process the landing area images acquired at each sampling time, the process is as follows:

[0092] Step 201, landing area image processing at the initial sampling time: using the processor to process the landing area image acquired by the image acquisition device at the initial sampling time, including the following steps:

[0093] Step 2011, Harris corner point e...

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Abstract

The invention discloses a vector constraint-based random characteristic point selection method for landing position detection. The method comprises the steps of 1, performing acquisition and synchronous uploading of a landing region image; and 2, processing the landing region image: 201, processing the landing region image at an initial sampling moment; 202, processing the landing region image at the next sampling moment by Harris corner extraction, Harris corner matching, SIFT characteristic extraction, SIFT characteristic point matching, characteristic point fusion, characteristic point combination generation and optimal characteristic point combination screening; and 203, returning to the step 202 of processing the landing region image at the next sampling moment. The method is simple in step, reasonable in design, convenient to realize, high in practicality and good in using effect; characteristic points for pose estimation can be simply, conveniently and quickly selected from characteristic points extracted from unknown landing region images; and the pose estimation precision can be effectively improved.

Description

technical field [0001] The invention belongs to the technical field of visual navigation, in particular to a random feature point selection method for landing position detection based on vector constraints. Background technique [0002] When UAVs perform rescue and search tasks, they are faced with the problem of emergency landing with unknown terrain in the drop zone, complex and no ground auxiliary navigation equipment guidance. Due to the cumulative error of inertial navigation and the susceptibility of GPS to interference, there are huge safety hazards when UAVs land in complex and unknown environments. Visual relative navigation has the advantages of simple equipment, large amount of information, strong concealment, and good autonomy. It is widely used in the fields of UAV autonomous landing / landing, autonomous refueling in the air, and spacecraft rendezvous and docking. Visual relative navigation has the advantages of strong autonomy, passiveness, and high guidance ac...

Claims

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Application Information

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IPC IPC(8): G06K9/52G06K9/46
CPCG06V10/464G06V10/42
Inventor 郝帅
Owner XIAN UNIV OF SCI & TECH
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