Semantic 3D UAV Inspection for Targeted Structure Scanning
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Solution Overview
Problem
Current 3D scan approaches for UAV-based structure inspection are inefficient as they require high-fidelity processing of large amounts of data, focusing on geometric reconstructions rather than semantic understanding, and often involve labor-intensive manual operation, which is imprecise and non-deterministic.
Innovation Solution
Implementing a multi-phase semantic 3D scan system where a UAV performs a first phase inspection to determine the semantic understanding and pose information of structure components, followed by a second phase inspection using a flight path determined by the UAV to capture detailed images of specific components, leveraging triangulation and camera pose information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-fidelity processing of large amounts of data is performed for geometric reconstruction, then measurement precision is improved, but loss of time increases and productivity decreases
Solution Approach 1:
The inspection process is divided into two phases: a first phase that captures comprehensive data for semantic understanding, and a second phase that focuses on detailed inspection of specific components. This segmentation allows the system to avoid processing all data at full fidelity simultaneously, reducing overall processing time while maintaining necessary precision for each phase
Solution Approach 2:
The patent extracts and prioritizes semantic information and pose information from the captured data, separating these critical elements from the full geometric dataset. By extracting only the necessary information for component identification and localization, the system reduces processing requirements while maintaining inspection quality
2Measurement precision
If comprehensive data capture is performed for complete structure inspection, then measurement precision is improved, but quantity of substance (data volume) increases
Solution Approach 1:
The first phase inspection performs preliminary data capture and semantic understanding before the second phase. This preliminary action identifies which components require detailed inspection, allowing the system to capture comprehensive data initially but then focus subsequent detailed capture only on relevant components, reducing total data volume
Solution Approach 2:
The system applies different data capture qualities to different components: high-fidelity capture is applied only to components identified as requiring detailed inspection, while other components receive standard capture. This local differentiation reduces overall data volume while maintaining necessary precision for critical components
3Ease of operation
If manual operation is used for UAV control, then ease of operation is improved, but productivity decreases and measurement precision worsens due to imprecision and non-determinism
Solution Approach 1:
The UAV system performs self-service through automated flight path execution and autonomous component targeting. Once the inspection parameters are set, the UAV autonomously navigates to capture points, positions itself according to determined camera poses, and captures images of identified components without continuous manual intervention, thereby maintaining ease of initial setup while dramatically improving productivity and precision
Solution Approach 2:
The system implements feedback loops where the UAV's captured images are processed to identify components and determine pose information, which then feeds back into automatic flight path generation and camera positioning. This closed-loop feedback enables automated control that improves both productivity and measurement precision while maintaining operational simplicity
Data Source
AI summary
Semantic three-dimensional scan is performed for the multi-phase inspection of a structure using an unmanned aerial vehicle (UAV). The multi-phase inspection includes a first inspection phase and a second inspection phase. A UAV performs the first inspection phase of the structure to determine a semantic understanding of components associated with the structure and pose information of the components. Based on the semantic understanding of the components and the pose information, a flight path indicating capture points and camera poses associated with the capture points is determined. The UAV then performs the second inspection phase of the structure according to the flight path, in which all or some of the components are inspected.