Multi-rotor unmanned aerial vehicle pose acquisition method based on markers in shape of large and small square

Abstract

The invention discloses a multi-rotor unmanned aerial vehicle (UAV) pose acquisition method based on markers in shape of a large and a small square. The method is as below: first determining target markers based on the relative height of the UAV and the markers, wherein the markers comprise a small square and a large square with side length 10 times of that of the small square; second, according to the determined target markers, establishing a relationship model between a CCD camera of the UAV and the target markers; and finally, according to the established model, employing a direct linear transformation method to obtain an azimuth angle of the UAV and location information of the UAV at the corresponding time. The method can accurately obtain the pose of the UAV.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, in particular to a multi-rotor unmanned aerial vehicle pose acquisition method based on large and small back characters markers. Background technique [0002] In recent years, with the frequent occurrence of large-scale natural disasters such as earthquakes, floods, and nuclear pollution, the research on small multi-rotor UAVs has gradually become a hot spot in UAV research. Especially in the autonomous navigation and landing of small multi-rotor UAVs, how to obtain the pose information of small multi-rotor UAVs more accurately is extremely important. The most widely used in recent years is to measure the position and orientation information of drones through the combination of GPS and IMU (inertial navigation equipment). However, the application of GPS has great limitations: it can only be detected outdoors and in the presence of interference signals. The man-machine is damage...

AI Technical Summary

Problems solved by technology

However, the application of GPS has great limitations: it can only be detected outdoors and in the presence of interference signals. The damage of the man-machine, and the IMU is expensive, which affects economic benefits

This method needs to acquire a large number of pictures in advance, process and analyze them, and then compare them with the pictures acquired in real time. The workload is heavy and the application value is not high.

Images