Aircraft Docking Guidance via Machine Vision Tracking
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Solution Overview
Problem
Current aircraft docking guidance systems, particularly visual perception types, face challenges in accuracy, adaptability to weather and illumination conditions, and reliability, necessitating improved methods for aircraft acquisition, tracking, positioning, and model identification.
Innovation Solution
A machine vision-based method and system that configures the aircraft berthing scene, performs image pre-processing, captures and tracks aircraft features like engines and front wheels, calculates deviation from guide lines, and verifies aircraft identity through template matching and similarity analysis, enhancing accuracy and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If visual perception type guidance system is used, then adaptability to weather and illumination conditions deteriorates, but system complexity and cost are reduced
Solution Approach 1:
The patent combines multiple detection methods (laser ranging, visual perception, and other sensors) into a unified guidance system that can adaptively select and integrate different sensing approaches based on environmental conditions, thereby improving weather and illumination adaptability while maintaining manageable system complexity through coordinated multi-sensor operation
Solution Approach 2:
The system dynamically adjusts its operational mode and sensor selection based on real-time weather and illumination conditions, transitioning between different guidance approaches (such as switching between visual perception and laser ranging) to maintain optimal performance across varying environmental scenarios
2Measurement precision
If visual perception type guidance system is used, then measurement precision of aircraft positioning is improved, but adaptability to weather conditions deteriorates
Solution Approach 1:
The patent introduces laser ranging technology as an intermediary measurement method that operates effectively under various weather conditions including fog, rain, and snow where visual perception systems fail, providing reliable distance and position data that complements visual perception to maintain high measurement precision across all environmental scenarios
Solution Approach 2:
The system changes operational parameters by switching between different sensing modalities (visual perception for clear conditions, laser ranging for adverse weather) based on environmental parameters, thereby maintaining high positioning accuracy regardless of weather or illumination conditions
3Speed
If buried induction coil type system is used, then response speed and cost are improved, but measurement accuracy and reliability deteriorate
Solution Approach 1:
The patent replaces the mechanical buried induction coil system with optical and laser-based sensing technologies that provide both high response speed and high measurement accuracy, eliminating the accuracy and reliability limitations of electromagnetic induction while maintaining the fast response characteristic
4Ease of manufacture
If buried induction coil type system is used, then cost is reduced, but reliability and measurement accuracy deteriorate
Solution Approach 1:
The patent substitutes expensive and unreliable buried induction coils with solid-state optical sensors and laser ranging devices that offer superior reliability and accuracy without requiring ground installation, thereby achieving long-term cost effectiveness through reduced maintenance and higher operational reliability
Data Source
AI summary
A machine vision-based method and system for aircraft docking guidance and aircraft type identification, comprising: S1: a monitoring scenario is divided into different information processing function areas; S2: a captured image is pre-processed; S3: the engine and the front wheel of an aircraft are identified in the image, so as to confirm that the aircraft has appeared in the image; S4: continuous tracking and real-time updating are performed on the image of the engine and the front wheel of the aircraft captured in step S3; S5: real-time positioning of the aircraft is implemented and the degree of deviation of the aircraft with respect to a guide line and the distance with respect to a stop line are accurately determined; S6: the degree of deviation of the aircraft with respect to the guide line and the distance with respect to the stop line of step S5 are outputted and displayed.


