Intelligent tracking flight system and method of unmanned aerial vehicle (UAV)

Abstract

The invention relates to an intelligent tracking flight system and method of a UAV, and belongs to the field of intelligent autonomous navigation of the UAV. The flight system comprises an image acquisition unit for image acquisition, a flight attitude measurement unit for detecting a flight inertia, a neural network processing unit for neural network processing and a control unit for control flight motion of the UAV; an image collected by a camera in the front of the UAV serves as input, the input is identified by the convolutional neural network, and an obstacle avoidance strategy is given.In the flight process, the alight attitude measurement unit based on a tunnel magnetic resistance effect characterized by high response is used to obtain key change position of the flight attitude ofthe UAV, the image acquisition unit is started to capture key images, a stereoscopic model of the flight environment is formed, key position images are provided for the UAV tracking flight path, and the integrated safety of the UAV tracking flight is improved.

Description

technical field [0001] The invention relates to the field of intelligent autonomous navigation of unmanned aerial vehicles, in particular to an intelligent tracking flight system and method for unmanned aerial vehicles. Background technique [0002] At present, the core research problem of intelligent UAV is the research of positioning and obstacle avoidance. The obstacle avoidance function is one of the indispensable key indicators to measure the intelligence of intelligent drones. In order to realize autonomous obstacle avoidance during the walking process of the intelligent UAV, the problem to be solved is: on the one hand, the external environment information of the robot is required, and on the other hand, it is required to be able to transform the acquired environmental information into control information. The camera on the UAV will collect the image in front of the UAV, and then the image recognition module based on the convolutional neural network will recognize t...

AI Technical Summary

Problems solved by technology

In order to realize autonomous obstacle avoidance during the walking process of the intelligent UAV, the problem to be solved is: on the one hand, the external environment information of the robot is required, and on the other hand, it is required to be able to transform the acquired environmental information into control information

However, the UAVs currently on the market have not yet encountered such problems in terms of tracking methods.

[0004] Further, in t...

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