Target tracking method for tracking ground moving target by unmanned aerial vehicle

Abstract

The invention discloses a target tracking method for tracking a ground moving target by an unmanned aerial vehicle, and the method comprises the steps: detecting the moving target through OpenCV, andcalculating a direction and speed instruction which should be executed by the unmanned aerial vehicle through employing a type-2 fuzzy logic controller according to the position information of the target on an image obtained by an airborne camera; and finally, controlling the unmanned aerial vehicle to continuously update the instruction so as to realize continuous tracking of the moving target. According to the method, the complexity of the tracking environment is considered, the traditional target detection method is combined, the uncertainty can be better processed by using the type-2 fuzzylogic control theory, and finally, the continuous tracking of the unmanned aerial vehicle to the ground moving target is realized.

Description

technical field [0001] The invention belongs to the technical field of autonomous tracking and control of unmanned aerial vehicles, and in particular relates to a target tracking method for an unmanned aerial vehicle to track a moving target on the ground. Background technique [0002] With the maturity of low-altitude UAV (Unmanned Aerial Vehicle, UAV) hovering, battery life, and gimbal technology, as well as the rise of computer vision (Computer Vision) and deep learning (Deep Learning), target tracking based on UAV platforms has It has become a research hotspot at home and abroad, and has been used in the tracking of criminal vehicles in urban anti-terrorism and the tracking of ground mobile targets in air combat. Tracking UAV refers to the use of airborne pan / tilt and other sensors to collect image information, and obtain the position information of the target on the image through the target detection process (or predict the position information of the target through sta...

AI Technical Summary

Problems solved by technology

[0006] 2) Uncertainty of actuator characteristics, that is, changes in control input due to changes in the characteristics of the actuator due to wear, environment, etc.;

[0008] 4) Uncertainty in the operating environment, that is, changes in the operating conditions of the system lead to changes in the corresponding input and output

[0009] It can be seen that T1-FLC has limitations in dealing with uncertainties. From a theoretical analysis, its limitations are mainly reflected in the fact that it uses T1-FSs represented by precise membership functions, and these T1-FSs cannot directly deal with the uncertainty of fuzzy rules

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