Sensor Pod Calibration via Rotational Imaging for Wheel Alignment
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Solution Overview
Problem
There is a need for a methodology to easily and efficiently calibrate alignment measurement systems that combine 3D machine vision and conventional measurement technologies, as existing methods are complex and not well-suited for field use.
Innovation Solution
A method involving a sensor pod with an image sensor that images targets on vehicle wheels, allowing for calibration using conventional fixtures by rotating the pod to capture images in multiple positions and processing these images to determine the axis of rotation, enabling accurate alignment calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D machine vision wheel alignment systems use conventional calibration fixtures and techniques, then the calibration process becomes complex and difficult to perform in the field, but the system maintains measurement precision
Solution Approach 1:
The patent creates a virtual copy of the calibration fixture in the computer's memory by processing images captured at multiple rotational positions. The algorithm reconstructs the three-dimensional geometry of the physical calibration fixture from two-dimensional images, creating a digital model that can be used for calibration calculations without requiring the physical fixture to remain in place or be perfectly replicated.
Solution Approach 2:
The patent replaces complex mechanical calibration procedures with an optical imaging and computational approach. Instead of using physical measurement tools and manual adjustment mechanisms, the system uses image capture, rotational positioning, and computer algorithms to determine alignment parameters, substituting mechanical complexity with optical and computational simplicity.
2Productivity
If 3D machine vision wheel alignment systems implement field calibration capabilities, then calibration efficiency improves, but the system complexity increases
Solution Approach 1:
The patent makes the sensor pod universally applicable by integrating multiple functions into a single device. The sensor pod can capture images of calibration fixtures, track wheel targets, and perform both calibration and alignment measurements using the same hardware and software platform, eliminating the need for separate calibration equipment and procedures.
Solution Approach 2:
The system performs self-calibration by using its own imaging sensors to capture images of the calibration fixture, process these images through algorithms, and automatically calculate the calibration parameters without requiring external measurement tools or complex manual procedures. The system serves its own calibration needs using integrated capabilities.
3Measurement precision
If the sensor pod captures images in multiple rotational positions, then the accuracy of determining the axis of rotation improves, but the calibration time increases
Solution Approach 1:
The patent uses periodic rotational positioning of the sensor pod at specific angular intervals (e.g., 0°, 90°, 180°, 270° or other predetermined positions) to capture images of the calibration fixture. This periodic sampling approach provides sufficient geometric information to accurately determine the axis of rotation while minimizing the number of positions required, thus balancing accuracy with time efficiency.
Data Source
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AI summary
A method is provided for calibrating a sensor pod of a wheel alignment system, the sensor pod including a housing rotatably mounted on a spindle, and an image sensor in the housing having a viewing axis oriented in a direction substantially normal to an axis of rotation of the spindle for imaging a target affixed to an object such as a vehicle wheel. An example of the method includes mounting the pod on a fixture via the pod spindle such that the pod spindle is stationary, and positioning a target to allow imaging of the target with the pod image sensor. The pod is rotated such that its image sensor obtains images of the target in at least two rotational positions, and the images of the target at the at least two rotational positions are processed to determine the location of the axis of rotation of the spindle relative to the image sensor.