Aerial Mapping Pose Estimation With Reduced Frame Overlap
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Solution Overview
Problem
Current aerial mapping technologies with unmanned aerial vehicles (UAVs) require significant frame overlap for accurate mapping, leading to high computational processing demands and limited real-time processing capabilities, which restricts rapid user feedback and adaptability during flights.
Innovation Solution
A method for improved aerial mapping that generates orthomosaic and point cloud data with reduced frame overlap by robustly determining camera pose changes through feature matching and telemetry data, enabling near-real-time processing and user feedback, and facilitating rapid generation of aerial maps and analyses using a single UAV or a fleet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional aerial mapping methods are used with significant frame overlap, then accurate image stitching is achieved, but computational processing demands increase and real-time processing capability is limited
Solution Approach 1:
The patent segments the aerial mapping process into distinct phases: capture phase with minimal overlap, initial processing phase for rapid subassembly generation, and final integration phase for complete mosaic creation. This segmentation allows different processing intensities at different stages, reducing overall computational demands while maintaining stitching accuracy.
Solution Approach 2:
The system performs preliminary actions by generating rapid initial image subassemblies during flight using reduced-frame overlap methods. These preliminary subassemblies are then integrated later, allowing real-time processing capabilities to be utilized effectively without requiring significant frame overlap that would increase computational complexity.
2Measurement precision
If traditional aerial mapping methods are used with significant frame overlap, then accurate image stitching is achieved, but processing time increases and user interaction during flight is limited
Solution Approach 1:
The mapping process is divided into segments that can be processed independently and in parallel. Image subassemblies are generated from captured frames during flight, allowing processing to occur concurrently with data collection rather than sequentially after completion, significantly reducing total processing time.
Solution Approach 2:
The system maintains continuous useful action by enabling real-time generation and integration of image subassemblies during the aerial survey flight. This continuous processing allows user interaction and mission adjustment during flight while maintaining stitching accuracy, eliminating the traditional sequential workflow.
3Productivity
If reduced frame overlap is used, then real-time processing capability is improved, but image stitching accuracy may be compromised
Solution Approach 1:
The system performs preliminary actions by capturing images with reduced overlap and generating initial image subassemblies during flight. These preliminary results are then refined through subsequent integration with additional data, achieving both real-time processing capability and accurate final stitching results.
Solution Approach 2:
The system implements feedback mechanisms where initial image subassemblies are generated in real-time, evaluated for quality, and used to guide subsequent capture and processing decisions. This feedback loop ensures stitching accuracy is maintained while enabling real-time processing capability.
Data Source
AI summary
A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.