Noise-Pattern Marker Tracking for Precise 6D Object Positioning
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Solution Overview
Problem
Existing position determination systems struggle to provide accurate and reliable 6D position measurement, particularly in large working volumes with significant distances between the measuring system and the object, often leading to inaccuracies and computational inefficiencies.
Innovation Solution
A camera-based system and method using a flat marker divided into individual fields with statistical noise patterns, employing correlation-based image analysis to determine the object's position, which includes a rough and fine determination process to enhance precision and reduce computational effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors (optical encoders, capacitive sensors, eddy current sensors) are used for position determination, then measurement precision can be maintained, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces complex mechanical and electrical sensors (optical encoders, capacitive sensors, eddy current sensors) with a camera-based optical system. The camera captures images of a marker with statistical noise patterns, and correlation-based image analysis determines position. This substitution eliminates the need for complex sensor assemblies while maintaining measurement precision through computational methods.
Solution Approach 2:
The patent uses a visual copy (image) of the marker instead of direct physical measurement. The camera captures an optical copy of the marker's noise patterns, and correlation analysis of this image data provides position information. This copying approach simplifies the measurement system by replacing physical sensor-contact methods with non-contact optical imaging.
2Device complexity
If image-based position determination is used in large working volumes, then device complexity is reduced, but measurement precision deteriorates due to large distances between measuring system and object
Solution Approach 1:
The patent applies local quality by placing statistical noise patterns specifically on the marker surface rather than relying on general environmental features. These localized high-contrast noise patterns provide distinctive local features that can be reliably detected and correlated even from large distances, maintaining precision while using a simple camera-based system.
Solution Approach 2:
The patent changes the parameters of the marker by using statistical noise patterns with specific bandwidth characteristics. The high-bandwidth noise patterns provide sufficient contrast and detail that remain detectable over large distances. The correlation-based analysis processes these specific parameter characteristics to maintain measurement precision despite the large working volume.
3Measurement precision
If high-resolution image analysis is performed to improve position determination accuracy, then measurement precision improves, but computational effort and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-defining the statistical noise patterns on the marker before the measurement process. These pre-established patterns with known statistical properties allow the correlation-based analysis to efficiently compare captured images against expected patterns, reducing computational effort compared to analyzing arbitrary high-resolution features.
Solution Approach 2:
The patent changes the parameters of the noise patterns to optimize the balance between precision and computational efficiency. By controlling the bandwidth and statistical properties of the noise patterns, the system achieves sufficient measurement precision while the correlation-based analysis remains computationally efficient compared to full high-resolution image processing.
4Measurement precision
If statistical noise patterns with high bandwidth are used on the marker, then position determination precision improves, but aliasing effects and computational complexity increase
Solution Approach 1:
The patent carefully controls the parameters of the statistical noise patterns, specifically the bandwidth. By optimizing the bandwidth parameter, the system achieves high measurement precision through sufficient pattern detail while avoiding excessive high-frequency content that would cause aliasing and require complex computational handling. The bandwidth is tuned to match the camera's resolution and the working distance.
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 and efficient 6D position determination of moving objects, even in large volumes, by utilizing high-bandwidth noise patterns and multiple cameras to minimize aliasing and ambiguity, ensuring accurate localization and orientation.
Implementation Method 1
The image acquisition unit (18) has an image sensor (22) and is arranged to image the marker (16) onto the image sensor (22)
Data Source
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AI summary
The invention relates to a system for the determination of the position of a movable object (12) in space, said system comprising a marker (16) to be attached to the object (12), said marker having a surface (30) which is subdivided into a plurality of individual fields (32), wherein the fields (32) each comprise a statistical noise pattern (34). The system further comprises an image capture unit (18) remote from the object (12), which unit is disposed to capture an image (28) of the marker (16), and an image evaluation unit (26), in which a reference image of the noise pattern (34) is stored. The image evaluation unit is designed to locate at least one of the fields (32) in the image (28) of the marker (16) currently detected by comparison with the reference image in order to determine a current position of the marker (16) in the space. The invention further relates to a corresponding method for determining a position, and to the marker (16).