3D Object Measurement Using Structured Light and Surface Mapping
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Solution Overview
Problem
Existing methods for measuring physical objects fail to detect the properties of surface regions between uniquely identifiable points, limiting the precision of shape detection and requiring additional techniques for quality assessment, such as detecting small surface damage.
Innovation Solution
A method and device that captures light beam bundles reflected on an object's surface, generates a second point cloud for surface quality, and combines it with a first point cloud using uniquely identifiable points as reference, utilizing a robot arm-mounted camera and illuminating device to guide over the object's surface, and employs structured light and photometric stereo analysis under different illumination scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only uniquely identifiable points are measured photogrammetrically, then the shape of the object can be detected, but the surface quality and properties of surface regions between markings are not detected
Solution Approach 1:
The measurement process is segmented into two distinct phases: first capturing uniquely identifiable points for shape reconstruction, then capturing light beam bundles reflected from surface regions for quality assessment. This segmentation allows each phase to optimize for its specific purpose while collectively achieving both shape and surface quality detection.
Solution Approach 2:
The invention transitions from two-dimensional point-based photogrammetry to three-dimensional light beam bundle analysis by capturing reflected light bundles from surface regions. This dimensional expansion enables detection of surface geometry and quality properties that were invisible in the original point-cloud approach.
2Measurement precision
If multiple illuminating devices and cameras are used for comprehensive surface detection, then surface quality detection precision is improved, but device complexity and hardware requirements increase
Solution Approach 1:
The camera system is designed to perform multiple functions: capturing uniquely identifiable points for shape reconstruction and capturing reflected light beam bundles for surface quality assessment. This multi-functionality eliminates the need for separate dedicated sensors for each measurement type, reducing overall device complexity.
Solution Approach 2:
Reflected light beam bundles serve as an intermediary that carries information about both the uniquely identifiable points and the surface regions between them. By analyzing this reflected light, the system extracts surface quality information without requiring direct contact or additional specialized sensors.
3Productivity
If the camera and illuminating device are mounted on a robot arm for automated measurement, then measurement efficiency and coverage are improved, but the system requires precise positioning and control infrastructure
Solution Approach 1:
The camera and illuminating device are merged into a single integrated measurement head mounted on the robot arm. This combination ensures that both components move together as one unit, maintaining fixed spatial relationships between them during automated scanning, which simplifies positioning control compared to coordinating separate devices.
Solution Approach 2:
The system uses the captured image data of reflected light beam bundles as feedback to reconstruct the three-dimensional surface geometry and detect surface quality. This feedback loop enables real-time adjustment and verification of measurement accuracy during automated operation.
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 precise mapping of object surface geometry and quality, allowing for detailed analysis of the object's shape and properties, including detection of defects like scratches, with improved processing speed and reduced hardware requirements.
Implementation Method 1
light beam bundles reflected on a surface of the object are captured as image data
Implementation Method 2
a surface geometry of the surface is detected by means of a structured light process on the basis of deviations of the generated image data of the pattern superimposed on the object from the known pattern
Implementation Method 3
the surface quality is determined from the image data acquired under different illumination scenarios by means of photometric stereo analysis
Data Source
AI summary
A method and a device for measuring a physical object, wherein image data of uniquely identifiable points on the object is captured from different perspectives by means of at least one camera, and a spatial position of the uniquely identifiable points are ascertained from this image data, and at least one three-dimensional point cloud of the uniquely identifiable points is created as a global map of the object. To detect a surface quality of the object, light beam bundles are reflected on a surface of the object and are captured as image data. The image data obtained from the light beam bundles reflected on the surface of the object comprises at least some of the uniquely identifiable points as well as surface regions located between the uniquely identifiable points.