UAV Multi-Camera Auto-Return Using Selected Visual Features
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Solution Overview
Problem
Aerial vehicles using a single camera face challenges in auto-returning due to differences in image recording when changing directions, which can prevent effective visual cognition for navigation.
Innovation Solution
Equipping aerial vehicles with multiple cameras facing different directions to provide comprehensive 360-degree coverage, allowing for reliable image data collection and navigation using selected features for auto-return, reducing processing and storage demands by storing only relevant image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single camera is used for aerial photography, then the device complexity is reduced, but the auto-return reliability deteriorates due to inability to capture images in all directions
Solution Approach 1:
The patent divides the single camera system into multiple cameras, each responsible for capturing images in specific directions (front, back, left, right). This segmentation allows the system to overcome the limitation of a single camera's fixed field of view and enables reliable auto-return by providing comprehensive environmental coverage from all orientations
Solution Approach 2:
The patent makes the camera system multi-functional by equipping the aerial vehicle with multiple cameras that can capture images in various directions simultaneously. This universal coverage ensures that regardless of the vehicle's orientation during return flight, the appropriate camera will capture the necessary visual information for navigation
2Reliability
If multiple cameras are equipped on the aerial vehicle, then the auto-return reliability is improved through comprehensive image coverage, but the processing and storage burden increases
Solution Approach 1:
The patent extracts only the essential visual information from the multiple camera feeds by identifying and storing key feature points rather than processing entire images. This extraction approach maintains the reliability benefits of multiple cameras while dramatically reducing the processing and storage burden by focusing only on salient navigational features
Solution Approach 2:
The patent applies partial action by selectively processing only certain images or image regions from the multiple cameras rather than analyzing all image data in full detail. This approach maintains sufficient visual information for reliable navigation while reducing overall computational load
3Measurement precision
If all image data from multiple cameras is stored, then the visual cognition accuracy is improved, but the memory storage requirement increases
Solution Approach 1:
The patent extracts only the critical visual information needed for navigation by identifying feature points in the images captured by multiple cameras. Instead of storing complete images, only these extracted feature points are stored, maintaining visual cognition accuracy while minimizing storage requirements
Solution Approach 2:
The patent changes the parameter of data representation from storing complete image data to storing condensed feature point data. This parameter transformation preserves the essential visual information needed for accurate navigation while dramatically reducing the quantity of stored data
Data Source
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AI summary
Systems and methods for vision-based auto-return are provided for an unmanned aerial vehicle (UAV) (100, 410) traversing an environment. The UAV (100, 410) may comprise multiple cameras (120a, 120b, 120c, 120d, 220, 415) with different orientations that may capture different fields of view (130a, 130b, 415). Image data collected by the multiple cameras (120a, 120b, 130c, 120d, 220, 415) may be stored or used for navigational aid, such as performing the auto-return. A selected portion of the image data, such as selected image features, may be stored or used for auto-return.