UAV Camera Tracking Control Without External Sensors
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Solution Overview
Problem
Current unmanned aerial vehicle (UAV) tracking technologies face stability and range limitations due to reliance on external sensors and communication modules when tracking moving targets.
Innovation Solution
A method and apparatus for UAVs equipped with a photographing device, including a gimbal and camera, that uses machine vision to identify and lock targets, adjusting the UAV's state and camera parameters in real-time to maintain the target on a display screen, independent of external sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless ranging sensors and communication modules are used for tracking, then tracking functionality is achieved, but stability and reliability deteriorate
Solution Approach 1:
The patent extracts and removes the dependency on external wireless ranging sensors and communication modules from the tracking system. Instead, it uses only the photographing device (camera) mounted on the UAV to capture images and perform machine vision-based target identification and tracking, thereby eliminating the instability caused by external sensor dependencies
Solution Approach 2:
The UAV equips itself with a photographing device that performs both target acquisition and tracking functions independently. The system uses onboard image processing and machine vision algorithms to identify, lock, and track targets without requiring external communication modules or ranging sensors, making the system self-sufficient and more reliable
2Measurement precision
If machine vision and real-time adjustment are implemented, then target identification accuracy improves, but system complexity increases
Solution Approach 1:
The photographing device serves multiple functions: it captures images for target identification, provides visual feedback for tracking, and enables machine vision processing. The same camera system is used for both acquisition and tracking phases, reducing the need for separate specialized components and managing complexity through multi-functional design
Solution Approach 2:
The system implements real-time feedback by continuously capturing images, processing them through machine vision algorithms, and adjusting the UAV's flight state and photographing device parameters based on target position information. This closed-loop feedback mechanism maintains high identification accuracy while managing complexity through iterative optimization
3Reliability
If the photographing device continuously adjusts to maintain target on screen, then tracking reliability improves, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts the photographing device parameters (such as focal length, aperture) and UAV flight state based on real-time target position and movement. Instead of continuous maximum-power operation, the system adapts its resource usage to the actual tracking requirements, maintaining reliability while optimizing energy consumption through dynamic parameter adjustment
Data Source
AI summary
Embodiments of the disclosure disclose a method and an apparatus for tracking a moving target and an unmanned aerial vehicle. The method includes: identifying and locking a moving target; and adjusting a moving state of the unmanned aerial vehicle and/or parameters of the photographing device according to a moving state of the moving target, so that the moving target is always located on a display screen of a control terminal. A method and an apparatus for tracking a moving target and an unmanned aerial vehicle provided in the disclosure can adjust the moving state of the unmanned aerial vehicle and/or the parameters of the photographing device in real time according to the moving state of the moving target and can ensure that the moving target in a preset size is always located on the display screen of the control terminal.