Drone Image Capture Feedback for Complete 3D Reconstruction
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Solution Overview
Problem
Human inspection of assets is time-consuming, labor-intensive, and often impractical due to location, size, or complexity, especially when it involves inaccessible areas or requires repetitive scheduling, leading to inefficiencies in defect detection and maintenance.
Innovation Solution
A method utilizing drones to execute flight plans for image data acquisition, with a visual feedback loop to determine data sufficiency for 3D model reconstruction, allowing for additional data collection where necessary, and employing structured light for feature matching and surface characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human inspectors manually inspect assets, then detailed defect detection is possible, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual human inspection with an automated system comprising a mobile platform, imaging devices, and computer processing. The system captures images of asset surfaces, automatically processes them through defect detection algorithms, and generates reports without human intervention during the inspection process, thereby reducing time loss while maintaining detection accuracy
Solution Approach 2:
The inspection system performs self-service by autonomously navigating to asset locations, capturing images, processing defect detection, and generating inspection reports without requiring human inspectors. The automated defect detection algorithm independently analyzes images and identifies defects, eliminating the need for manual inspection labor
2Reliability
If human inspectors are deployed to inaccessible areas, then complete asset coverage is achieved, but the complexity and difficulty of operation increase
Solution Approach 1:
The patent replaces human inspectors with a mobile automated inspection platform that can navigate to and inspect inaccessible asset areas. The system uses automated navigation and imaging devices to capture images of surfaces that would be difficult or dangerous for humans to access, thereby improving inspection completeness while eliminating operational difficulties associated with human access
Solution Approach 2:
The system creates visual copies (images) of inaccessible asset surfaces by positioning imaging devices to capture images of areas that would be difficult for humans to directly observe. These image copies allow complete asset coverage to be achieved remotely without requiring physical human access to dangerous or inaccessible locations
3Loss of information
If multiple inspection visits are scheduled to ensure complete data acquisition, then data completeness improves, but productivity decreases
Solution Approach 1:
The patent performs preliminary actions by capturing all necessary images during a single inspection visit and pre-processing them to assess data sufficiency for 3D reconstruction. The system identifies areas with insufficient data and automatically plans additional imaging passes during the same visit, ensuring complete data acquisition in one go rather than requiring multiple separate visits, thereby maintaining data completeness while improving productivity
Solution Approach 2:
The inspection system maintains continuous useful action by seamlessly transitioning between capturing initial images, assessing data sufficiency, and performing additional targeted imaging passes all during a single inspection visit. This continuous operation ensures complete data acquisition without interrupting the inspection workflow or requiring the asset to be re-visited, thereby eliminating productivity losses associated with multiple inspection visits
4Manufacturing precision
If high-resolution image data is acquired at all geometric poses, then 3D model reconstruction quality improves, but the quantity of data and processing complexity increase
Solution Approach 1:
The patent applies local quality by differentiating between regions that require high-resolution imaging and those that do not. The system identifies areas with sufficient data for accurate 3D reconstruction and focuses high-resolution imaging only on regions with insufficient data, rather than uniformly applying high resolution across all areas. This selective approach maintains 3D model accuracy while reducing overall data quantity and processing complexity
Solution Approach 2:
The system dynamically changes imaging parameters based on real-time assessment of data sufficiency. When insufficient data is detected for a particular region, the system adjusts parameters such as resolution and imaging angles for subsequent passes focused on that region. This adaptive parameter adjustment ensures adequate data quality for 3D reconstruction while minimizing unnecessary high-resolution data collection, thereby reducing processing complexity
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
Enables efficient and automated generation of 3D models of assets, reducing the need for human intervention and improving inspection efficiency by ensuring complete data acquisition in a single visit, thus enhancing defect detection and maintenance processes.
Implementation Method 1
employing structured light for feature matching and surface characterization
Data Source
AI summary
The present approach relates to an automatic and efficient motion plan for a drone to collect and save a qualified dataset that may be used to improve reconstruction of 3D models using the acquired data. The present architecture provides an automatic image processing context, eliminating low quality images and providing improved image data for point cloud generation and texture mapping.