Drone Landing Control for Tracking Moving Platforms
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Solution Overview
Problem
Existing drone landing systems struggle with guiding multi-rotor drones to accurately land on moving platforms due to the challenges of tracking and positioning in motion, leading to inefficiencies and reduced maneuverability.
Innovation Solution
A method and system that determine operating parameters of a moving platform using field-of-view images collected at different moments and flight parameters, calculating a time-varying tracking position to control the drone's landing operation, reducing reliance on real-time image collection and enhancing landing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time image collection is used to track the moving platform, then tracking accuracy is improved, but energy consumption and computational complexity increase
Solution Approach 1:
The patent applies periodic action by collecting images at specific time intervals (first moment and second moment) rather than continuous real-time collection. The control operation frequency is set higher than the visual recognition frequency, creating a periodic sampling pattern that reduces energy consumption while maintaining adequate tracking accuracy for the moving platform.
Solution Approach 2:
The patent uses preliminary action by pre-calculating the time-varying tracking position of the moving platform based on images collected at two different moments. This pre-computed trajectory information is then used to guide the drone's tracking, eliminating the need for continuous real-time image processing while maintaining accurate tracking throughout the approach.
2Measurement precision
If real-time image collection is used to track the moving platform, then tracking accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent reduces computational complexity by implementing periodic image collection at discrete time moments rather than continuous processing. By calculating tracking positions only at these periodic intervals and interpolating between them, the system achieves adequate tracking accuracy with significantly reduced computational burden compared to real-time processing.
Solution Approach 2:
The patent applies preliminary action by pre-computing the time-varying tracking position of the moving platform based on images from two moments. This pre-calculated trajectory serves as a reference for the entire tracking process, eliminating the need for complex real-time image processing and reducing overall computational complexity while maintaining tracking accuracy.
3Use of energy by moving object
If visual recognition operates at low frequency, then energy consumption is reduced, but landing accuracy deteriorates
Solution Approach 1:
The patent resolves this contradiction by using preliminary action to pre-calculate the complete time-varying tracking position of the moving platform based on images from two moments. This pre-computed trajectory provides accurate position information throughout the landing approach, ensuring high landing accuracy even though visual recognition operates at low frequency with reduced energy consumption.
Solution Approach 2:
The patent applies copying by creating a computational model of the moving platform's trajectory based on two image samples. This copied trajectory information is then used to guide the drone throughout the entire landing process, maintaining high accuracy without requiring continuous visual recognition, thus reducing energy consumption while preserving landing precision.
4Device complexity
If the platform is fixed at a certain position, then system complexity is reduced, but maneuverability deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed platform concept to a moving platform with time-varying position. The system calculates the platform's trajectory based on images collected at two different moments, enabling the platform to move dynamically during the drone's approach. This dynamic capability significantly improves maneuverability and versatility while the calculation-based approach keeps system complexity manageable.
Data Source
AI summary
The present disclosure provides a method for controlling a drone, a drone, and a system. The method for controlling a drone comprises: determining operating parameters of a moving platform according to field-of-view images containing the moving platform collected at any two different moments and flight parameters of the drone; calculating a time-varying tracking position of the moving platform based on the operating parameters; controlling the drone to track the moving platform according to the time-varying tracking position of the moving platform; and controlling the drone to perform a landing operation according to a relative position of the moving platform and the drone during tracking. The technical solutions according to the present disclosure have high landing accuracy, rely less on device performance and have high versatility.