Autonomous Robotic System for Aircraft Surface Inspection and Processing
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Solution Overview
Problem
Current robotic systems face challenges in efficiently and accurately processing three-dimensional surfaces, particularly in removing paint from complex shapes like aircraft fuselages and wings, due to environmental uncertainties and the need for precise control over surface processing devices.
Innovation Solution
The system employs multi-spectral machine vision components and a high-power laser scanner to gather and process data on surface properties, using a Surface Property Analyzer, Surface Model, Surface Process Planner, and Surface Coverage Planner to precisely maneuver and modulate the processing device, ensuring accurate and efficient coverage of the surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot processes the entirety of a three-dimensional surface, then complete coverage is achieved, but the complexity of planning and control increases significantly
Solution Approach 1:
The system segments the three-dimensional surface into multiple two-dimensional patches, which are then further divided into grid cells. This hierarchical segmentation transforms the complex 3D coverage problem into manageable 2D sub-problems, reducing planning complexity while ensuring complete surface coverage.
Solution Approach 2:
The system projects the 3D surface onto 2D patches and represents the coverage problem in a two-dimensional grid space. By changing the dimensional representation from 3D to 2D, the patent simplifies the computational complexity of path planning and control while maintaining coverage completeness.
2Manufacturing precision
If the robot adapts to environmental uncertainties and surface variations, then processing accuracy improves, but the computational requirements and system complexity increase
Solution Approach 1:
The system performs preliminary mapping of the three-dimensional surface geometry and properties before executing the coverage task. By pre-characterizing the surface and planning paths in advance, the robot can adapt to surface variations during execution without requiring complex real-time computation, thus maintaining precision while managing system complexity.
Solution Approach 2:
The system incorporates feedback mechanisms that allow the robot to sense surface properties during processing and adjust its behavior accordingly. This feedback loop enables adaptation to environmental uncertainties and surface variations, improving processing accuracy while the feedback-based approach keeps computational requirements manageable by using sensor data to guide decisions.
3Manufacturing precision
If the robot moves the processing device precisely over the surface, then processing quality improves, but the processing speed decreases
Solution Approach 1:
By segmenting the surface into patches and cells, the system can plan efficient paths that move systematically through each segment. This structured approach allows the robot to maintain precise positioning within each cell while minimizing unnecessary movements between segments, thereby improving both processing quality and speed.
Solution Approach 2:
The coverage planning algorithms generate continuous paths that minimize idle movements and keep the processing device continuously engaged with the surface. By eliminating unnecessary stop-and-start behavior and optimizing the sequence of cell visits, the system maintains high processing quality while improving overall processing speed and productivity.
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
This approach enables high-quality, efficient paint removal by accurately planning and executing surface processing maneuvers, adapting to surface geometry and properties, and ensuring complete coverage while respecting environmental and robotic constraints.
Implementation Method 1
the surface processing device is a high-power laser scanner, originally designed for laser welding, which is used to remove coatings from aeronautical surfaces
Implementation Method 2
the machine vision components are comprised of multi-spectral cameras with corresponding illumination sources that can discriminate between various layers of paint and underlying substrates
Data Source
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AI summary
The invention disclosed herein describes a supervised autonomy system designed to precisely model, inspect and process the surfaces of complex three-dimensional objects. The current application context for this system is laser coating removal of aircraft, but this invention is suitable for use in a wide variety of applications that require close, precise positioning and maneuvering of an inspection or processing tool over the entire surface of a physical object. For example, this system, in addition to laser coating removal, could also apply new coatings, perform fine-grained or gross inspection tasks, deliver and/or use manufacturing process tools or instruments, and/or verify the results of other manufacturing processes such as but not limited to welding, riveting, or the placement of various surface markings or fixtures.