UAV 3D Reconstruction With In-Flight Scan Plan Updates
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Solution Overview
Problem
Current unmanned aerial vehicle (UAV) systems lack the capability for efficient and autonomous scanning of complex three-dimensional targets with concavities, irregular surfaces, and oblique geometries, requiring manual operation and extensive human intervention for data review and additional scanning.
Innovation Solution
The implementation of a UAV system that autonomously scans three-dimensional targets by generating a lower-resolution 3D model, dynamically updating the scan plan, and improving resolution in real-time using onboard processors and image sensors, enabling reliable framing, robust feature detection, and reduced operator attention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual operation is used to scan complex three-dimensional targets, then the operator can review data and perform additional scanning, but the scanning process requires extensive human intervention and is less efficient
Solution Approach 1:
The UAV system performs self-service by autonomously navigating to predetermined locations, capturing images, and generating 3D models without continuous human intervention. The system independently executes the scanning mission based on pre-programmed instructions, only requiring initial task specification and final result review from the operator.
Solution Approach 2:
The system performs preliminary actions by pre-determining scan locations and generating mission plans before execution. The UAV autonomously navigates to predetermined locations based on pre-calculated trajectories, eliminating the need for real-time manual control during the scanning process.
2Measurement precision
If high-resolution scanning is performed on complex targets with concavities and irregular surfaces, then accuracy is improved, but the scanning time and data processing complexity increase
Solution Approach 1:
The scanning process is segmented into discrete mission segments, each targeting specific portions of the three-dimensional object. The UAV autonomously navigates to predetermined locations corresponding to different segments, capturing images systematically to ensure complete coverage of complex geometries including concavities and irregular surfaces.
Solution Approach 2:
The system dynamically adjusts the scanning process by autonomously selecting and executing mission segments based on the object's geometry. The UAV can adapt its flight path and imaging parameters in real-time to optimize coverage of complex features while maintaining high reconstruction accuracy.
3Reliability
If comprehensive scanning of large areas is performed, then complete data coverage is achieved, but the number of images and data processing requirements increase
Solution Approach 1:
The large-area scanning mission is divided into multiple discrete mission segments, each covering specific geographic zones or portions of the target area. The UAV executes these segments systematically, ensuring complete coverage while managing data volume through structured organization of captured images by location and segment.
Data Source
AI summary
In some examples, an unmanned aerial vehicle (UAV) may include one or more processors configured to capture, with one or more image sensors, and while the UAV is in flight, a plurality of images of a target. The one or more processors may compare a first image of the plurality of images with a second image of the plurality of images to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. In addition, the one or more processors may determine, based at least on the difference, and while the UAV is in flight, an update to a three-dimensional model of the target.