Abstract

This paper mainly studies how to use the stereo vision system that combines the monocular vision with parallel path search to locate the target. When the unmanned aerial vehicle (UAV) searches in the mission area according to the parallel path, the SSD image detection algorithm based on deep learning is adopted to detect and identify the target in the area. The image coordinate information is inversely calculated by using the pixel coordinate information fed back by machine vision. The auxiliary coordinate system is established according to the relationship of angle position between the track line and the basic coordinate system in the parallel path. Combining the position relation and the attitude direction information of UAV, the target position conversion relation between the imaging coordinate system and the auxiliary coordinate system is solved by using the direction cosine matrix. Combined with the coordinate information of UAV, the coordinate position of the target point in the basic coordinate system is finally solved through three coordinate conversion operations. In order to avoid the single calculating error of the target coordinates, the weighted average operation is carried out. On the basis of not changing the search trip of the parallel path, the target location function is preliminarily realized through the reverse solution and the weighted average operation of the target coordinates.

Highlights

  • At present, the application scopes and fields of target location are extensive, and machine vision is widely used to implement target location in all walks of life [1][2][4]

  • This paper employs a new way to carry out the target location by using monocular vision to construct the stereo vision system, and uses the stereo vision system combines the monocular vision with parallel path search to locate the target

  • This paper completes the process of unmanned aerial vehicle (UAV) target detection and recognition as well as target location and processing

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Summary

Introduction

The application scopes and fields of target location are extensive, and machine vision is widely used to implement target location in all walks of life [1][2][4]. Compared with multi-vision, monocular vision has less research on static target location. There are many limitations in target location using monocular vision, but monocular vision has its outstanding advantages, such as small computation, fast speed and economical benefit. Monocular vision can locate static targets by stereo vision algorithm. The evaluation of the machine vision target location algorithm is mainly reflected in three aspects: stability, location accuracy and location time-consuming. This paper employs a new way to carry out the target location by using monocular vision to construct the stereo vision system, and uses the stereo vision system combines the monocular vision with parallel path search to locate the target

Platform selection
E Camera O A detection area
UAV direction determination
Coordinate conversion
Weighted average of the target position
Summary and outlook
Full Text
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