Aerial Vehicle Camera Positioning for Close-Range Relative Localization
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Solution Overview
Problem
Current satellite- and barometer-based positioning systems lack the accuracy required for precise vertical and horizontal positioning of aerial vehicles, particularly in close proximity, which is essential for collision avoidance and navigation.
Innovation Solution
The method involves using camera systems on aerial vehicles to capture and compare image data, determining a geometric relation between the images to calculate the relative position of the vehicles with sub-meter accuracy, leveraging computer vision algorithms like the five-point or eight-point algorithm to identify features and calculate coordinates, and synchronizing camera systems for precise field-of-view overlap adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite- or barometer-based positioning systems are used for navigating aerial vehicles, then the positioning system is simple to implement and operate, but the accuracy in vertical direction and overall positioning accuracy is too low for some applications
Solution Approach 1:
The patent uses camera systems as intermediary devices to capture image data of the environment, which then serves as the basis for determining relative position. Instead of directly using satellite signals or barometer readings, the system mediates through optical image capture and geometric processing to achieve higher positioning accuracy without requiring complex satellite infrastructure
Solution Approach 2:
The patent replaces traditional mechanical/electronic positioning systems (satellite receivers, barometers) with an optical-based system using camera arrays. By substituting the measurement mechanism from direct sensor reading to optical image analysis with geometric processing, the system achieves superior vertical and horizontal positioning accuracy
2Measurement precision
If camera systems are used to capture image data for determining relative position, then the positioning accuracy is improved to sub-meter level, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent divides the positioning task into segments: multiple cameras capture images independently, then image processing identifies features separately, and finally geometric processing combines these results to determine relative position. This segmentation allows each component to be optimized independently while achieving high overall accuracy
Solution Approach 2:
The patent changes the fundamental parameter from direct distance measurement to angular/geometric relationship measurement through image analysis. By capturing images and processing geometric relations rather than directly measuring position, the system achieves higher precision with standard camera hardware
3Measurement precision
If geometric relation of image data is used to determine relative position, then sub-meter localization accuracy is achieved, but the computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary actions by having cameras continuously capture image data and pre-process images to identify features before actual positioning is needed. This allows the computationally intensive geometric processing to be performed on pre-processed data, reducing real-time processing requirements while maintaining high accuracy
Solution Approach 2:
The patent creates copies of the environment through image capture from multiple perspectives. By working with these optical copies rather than directly measuring physical distances, the system can perform geometric calculations on digital data, which is faster and more flexible than physical measurement methods
Data Source
AI summary
The present disclosure relates to a method for determining a relative position of a first aerial vehicle and at least one second aerial vehicle to each other. The method comprises receiving first image data of a first camera system attached to the first aerial vehicle and second image data of a second camera system attached to the second aerial vehicle. Further, the method provides for determining the relative position using a geometric relation of the first and the second image data.