Multi-DOF Vision System Calibration via Image-Based Position Compensation
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Solution Overview
Problem
Multi-degree-of-freedom vision systems face challenges in precisely determining the position relationship between the imaging element and the base due to limitations in mechanical processing and assembly techniques, leading to inaccuracies in calculating the exact positions of the imaging element and base during movements.
Innovation Solution
A calibration method for multi-degree-of-freedom movable vision systems, which involves using an imaging component with position acquisition devices, a calculation component, and a control component to capture images of a calibration template while recording position information, allowing for the calculation of precise relative positions and rotation/translation relationships between the imaging element and the base.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If mechanical processing and assembly techniques are used to mount the imaging component, then the system can be manufactured, but the precise position relationship between the imaging element and the base cannot be ensured due to manufacturing errors
Solution Approach 1:
The patent applies preliminary action by performing calibration before actual use. The calibration process pre-determines the position relationship between the imaging element and base by capturing images at multiple known positions and calculating transformation matrices. This preliminary calibration data compensates for manufacturing errors that cannot be avoided during assembly.
Solution Approach 2:
The patent replaces direct reliance on mechanical precision with a computational system. Instead of depending on perfectly machined mechanical components to achieve precise positioning, the system uses image processing, coordinate transformation algorithms, and calibration data to calculate and compensate for positional deviations, substituting mechanical precision requirements with computational correction.
2Adaptability or versatility
If the imaging element moves in multiple degrees of freedom, then the system achieves versatility and adaptability, but the position calculation becomes complex and inaccurate due to cumulative errors
Solution Approach 1:
The patent implements feedback by continuously capturing images of the calibration template at different positions and using these images to calculate and update transformation matrices. The system uses the actual observed positions from images to correct and refine the position calculations, creating a closed-loop feedback mechanism that compensates for cumulative errors across multiple degrees of freedom.
Solution Approach 2:
The patent transitions from direct mechanical coordinate measurement to image space coordinate measurement. By capturing images and extracting feature point coordinates from the calibration template, the system operates in an additional image dimension, allowing for more accurate position determination that is not constrained by mechanical axis alignment errors.
3Measurement precision
If direct calculation is used to determine the position of the imaging element, then the process is simple and fast, but the results are inaccurate due to mechanical assembly errors
Solution Approach 1:
The patent applies preliminary action by performing calibration before actual use. The calibration process pre-determines the position relationship between the imaging element and base by capturing images at multiple known positions and calculating transformation matrices. This preliminary calibration data compensates for manufacturing errors that cannot be avoided during assembly.
Solution Approach 2:
The patent introduces a calibration template as an intermediary object between the imaging element and the base. This template with known feature points serves as a reference mediator that allows the system to indirectly determine positions through image matching and coordinate transformation, rather than relying directly on mechanical position measurements.
Data Source
AI summary
In a calibration method for a multi-degree-of-freedom movable vision system, a calibration template is placed in front of a camera component, each degree of freedom of movement of the camera component is rotated, several images including features of the calibration template are recorded using the camera component, position information of each degree of freedom of movement when the corresponding images are acquired is also recorded, and calibration results of the camera component and each degree of freedom of movement are calculated using a calculation component. The movable vision system comprises the camera component, the calculation component and a control component.