Optical Tag Gradient Corners for Precise Boundary Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional optical tag detection systems introduce substantial imprecision, leading to incorrect pose estimation and potential operational failures, such as an aerial drone failing to land accurately due to misaligned boundary detection of up to 20 centimeters.
Innovation Solution
The implementation of high precision optical tags (HPOT) with gradient features, which include symmetrical gradient patterns at corners, allows for precise boundary determination by enhancing existing optical tag processing algorithms, improving accuracy to within a single pixel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optical tag detection algorithms are used, then the system is simple and resource-constrained devices can operate, but boundary detection accuracy deteriorates with misalignment up to 20 centimeters
Solution Approach 1:
The patent applies preliminary action by pre-configuring gradient features at the corners of the optical tag before detection. These gradient features are predetermined patterns that guide the detection algorithm to accurately identify corner locations. The gradient transitions from the corner color to the background color in a controlled manner, enabling the detection system to proactively locate corners with high precision rather than relying on post-detection correction of misaligned boundaries.
Solution Approach 2:
The patent utilizes color changes by implementing gradient features that exhibit gradual color transitions from the corner color to the background color. These gradient features create distinct visual patterns that enhance detectability. The color gradient provides a clear signal to the detection algorithm, allowing it to precisely identify corner locations by detecting the gradient boundaries, thereby improving measurement precision without significantly increasing device complexity.
2Measurement precision
If boundary detection accuracy is improved to within a single pixel, then pose estimation precision is enhanced, but the complexity of the detection system increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring gradient features at the corners of the optical tag before detection. These gradient features are predetermined patterns that guide the detection algorithm to accurately identify corner locations. The gradient transitions from the corner color to the background color in a controlled manner, enabling the detection system to proactively locate corners with high precision rather than relying on post-detection correction of misaligned boundaries.
Solution Approach 2:
The patent utilizes parameter changes by modifying the visual parameters of the optical tag corners through gradient features. The gradient features introduce controlled variations in color intensity and spatial distribution, creating distinct detectable patterns. This parameter modification enhances the detectability of corner locations without fundamentally changing the detection algorithm's core functionality, thereby improving pose estimation accuracy while limiting the increase in system complexity.
3Measurement precision
If gradient features are added to optical tags, then corner detection precision is significantly improved, but the manufacturing complexity of the tags increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring gradient features at the corners of the optical tag before detection. These gradient features are predetermined patterns that guide the detection algorithm to accurately identify corner locations. The gradient transitions from the corner color to the background color in a controlled manner, enabling the detection system to proactively locate corners with high precision rather than relying on post-detection correction of misaligned boundaries.
Solution Approach 2:
The patent utilizes parameter changes by modifying the visual parameters of the optical tag corners through gradient features. The gradient features introduce controlled variations in color intensity and spatial distribution, creating distinct detectable patterns. This parameter modification enhances the detectability of corner locations without fundamentally changing the detection algorithm's core functionality, thereby improving pose estimation accuracy while limiting the increase in system complexity.
Data Source
AI summary
An image of an optical tag may be acquired by a camera to extract tag data and determine a pose of the camera relative to the optical tag. The optical tag includes gradient features at the corners. These gradient features transition from one color near the corner of the optical tag to a second color distal to the corner of the optical tag. The image, once acquired, is analyzed to determine gradient values, identify the corners of the optical tag, and determine the boundaries of the optical tag. The contents of the optical tag may then be decoded to extract tag data. In addition, pose data may be determined to indicate a distance and an angle of the camera relative to the optical tag.