Photographing point positioning method based on unmanned aerial vehicle and related device

Abstract

The invention discloses a photographing point positioning method based on an unmanned aerial vehicle, and the method comprises the steps: obtaining the three-dimensional point cloud data of a target scene, and calibrating the coordinates of a feature point and the initial coordinates of a camera from the three-dimensional point cloud data; determining a horizontal projection direction vector between the camera initial coordinates and the feature point coordinates in a horizontal plane according to the feature point coordinates and the camera initial coordinates; determining a nose direction ofthe unmanned aerial vehicle according to the horizontal projection direction vector; and determining a horizontal unit vector of the projection direction according to the machine head direction. Theprojection direction vector can be corrected by reversely deducing the horizontal unit vector in the projection direction through the nose direction, and the feasible photographing point coordinates can be calculated according to the three-dimensional unit vector calculated by the horizontal projection direction vector, the feature point coordinates and the preset spatial distance, so that the efficient automatic positioning of the photographing point of the unmanned aerial vehicle is realized. The invention further provides a device, equipment and a storage medium, which also have the above beneficial effects.

Description

technical field [0001] The present invention relates to the technical field of UAV positioning, in particular to a method for locating a photo point based on a UAV, a device for locating a photo point based on a UAV, a device for locating a photo point based on a UAV, and a A computer readable storage medium. Background technique [0002] With the in-depth industrial application of UAV automatic track flight function in the fields of aerial surveying and mapping and electric energy, the point cloud data scanned by lidar has more and more outstanding advantages, and high-precision point cloud data can be combined with UAV gimbal parameters for trajectory planning. With the increase of business volume of 3D route planning, efficient route planning using 3D point cloud is an urgent problem to be solved. [0003] In the prior art, it is usually only manually calibrated to calibrate the position where the drone needs to fly in the 3D point cloud. The process of manual calibrat...

AI Technical Summary

Problems solved by technology

However, the process of manual calibration will bring uncertainty in the spatial position. At the same time, manually setting the camera position and camera parameters of each 3D point greatly reduces the efficiency of 3D route planning.

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