Camera Positioning Using Segmented Point Cloud Matching
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Solution Overview
Problem
Iterative Closest Point (ICP) matching techniques for large point clouds lead to increased processing time, potentially compromising real-time measurement capabilities in part assembly systems.
Innovation Solution
A measuring system that restricts the point cloud comparison to the camera's imaging range, using an RGB-D camera to measure depth information and compare it with pre-stored three-dimensional shape data, enhancing processing efficiency by reducing the number of point clouds to be matched and improving precision in calculating the camera's position and attitude.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ICP matching technique is applied to large point clouds, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent divides the large point cloud into multiple smaller regions based on spatial coordinates. The processor selectively performs ICP matching only on relevant regions containing the measurement target, rather than processing the entire point cloud. This segmentation approach maintains measurement precision while significantly reducing processing time by eliminating unnecessary computations on irrelevant point cloud areas.
Solution Approach 2:
The patent applies different processing strategies to different regions of the point cloud. High-precision ICP matching is applied locally to regions containing the measurement target, while other regions are processed with simpler methods or excluded from detailed matching. This local quality approach ensures precision where needed while reducing overall processing time.
2Productivity
If the number of point clouds to be matched is reduced, then processing time is reduced, but measurement precision may deteriorate
Solution Approach 1:
The patent performs preliminary actions by first identifying and selecting only the relevant regions containing the measurement target before performing ICP matching. This preliminary selection step ensures that the reduced set of point clouds to be matched still contains all necessary information for accurate measurement, thus maintaining precision while improving processing efficiency.
Solution Approach 2:
The patent extracts and isolates the relevant point cloud regions containing the measurement target from the larger point cloud dataset. By taking out only the necessary portions for matching, the system achieves both reduced processing time and maintained measurement precision, as the extracted regions contain sufficient information for accurate camera positioning.
Data Source
AI summary
A measuring system includes a processor. The processor calculates first information. The first information indicates a position and an attitude of a camera. The camera measures depth information along with an image of a measurement target. The processor extract second shape information from first shape information based on the first information. The first shape information indicates a three-dimensional shape of the measurement target. The second shape information indicates a three-dimensional shape corresponding to an imaging range of the camera. The processor calculates second information based on a result of a comparison between the depth information and the second shape information. The second information indicates the position and the attitude of the camera with a higher precision than the first information.