Multi-Camera Triangulation Ranging for Aircraft Ground Collision Avoidance
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Solution Overview
Problem
Commercial aircraft face significant challenges during ground operations due to collisions with objects, particularly with wingtips and engines, which are outside the pilot's field of view, leading to costly repairs and downtime, as existing systems lack effective collision avoidance capabilities for areas beyond the aircraft's cabin.
Innovation Solution
An object ranging system using two cameras and a light projector to capture and correlate images from distinct vantage points, employing structured light and triangulation to calculate the range of objects outside the aircraft, providing visual and audible alerts to pilots to avoid potential collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If pilots rely on visual observation from the cockpit, then they can observe objects directly in front of the cabin, but they cannot see objects behind and out of the field of view such as wingtips and engines
Solution Approach 1:
The system divides the monitoring function into multiple segments by using multiple cameras positioned at different locations (front, rear, and side cameras) to capture images from different viewpoints. This segmentation allows the system to overcome the limited field of view from the cockpit by distributing the observation task across multiple distributed sensors.
Solution Approach 2:
The system nests multiple camera systems within the aircraft structure, with cameras positioned on the fuselage, wings, and tail. This nested arrangement allows the monitoring system to be integrated into the existing aircraft without requiring a completely separate external observation system, thereby reducing overall complexity.
2Reliability
If a multi-camera triangulation system is implemented to detect objects behind wingtips and engines, then collision detection capability is improved, but system complexity and processing requirements increase
Solution Approach 1:
The system introduces an intermediary processing layer that automatically correlates images from multiple cameras and performs triangulation calculations. This intermediary processing function abstracts the complexity of multi-camera coordination and triangulation mathematics, presenting simplified collision risk information to the pilot without requiring them to manually process the complex image data.
Solution Approach 2:
The system replaces manual visual assessment by the pilot with an automated optical-mechanical system using cameras and image processing. This substitution uses electronic image capture and computational algorithms instead of human visual processing, improving reliability while managing complexity through automation.
3Measurement precision
If structured light is projected onto objects to enhance detection accuracy, then measurement resolution is improved, but energy consumption and system complexity increase
Solution Approach 1:
The light projector operates periodically rather than continuously, projecting structured light patterns at specific intervals during image capture. This periodic operation reduces energy consumption while still providing the necessary measurement precision for collision detection, as the structured light is only active when needed for triangulation calculations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and alerts pilots to potential collisions with wingtips and engines, reducing the risk of costly repairs and downtime by providing accurate range information and enhancing situational awareness during ground operations.
Implementation Method 1
a light projector to project structured light onto a scene
Implementation Method 2
two cameras to simultaneously capture images of the scene from two distinct vantage points
Data Source
Figure 1
Figure 2A~2B
Figure 3A
AI summary
Apparatus and associated methods relate to ranging an object nearby an aircraft by triangulation using two simultaneously-captured images of the object. The two images are simultaneously captured from two distinct vantage points on the aircraft. Because the two images are captured from distinct vantage points, the object can be imaged at different pixel-coordinate locations in the two images. The two images are correlated with one another so as to determine the pixel-coordinate locations corresponding to the object. Range to the object is calculated based on the determined pixel-coordinate locations and the two vantage points from which the two images are captured. Only a subset of each image is used for the correlation. The subset used for correlation includes pixel data from pixels upon which spatially-patterned light that is projected onto the object by a light projector and reflected by the object is focused.