Machine Vision Wheel Alignment Camera Calibration
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Solution Overview
Problem
Traditional machine vision vehicle wheel alignment systems require replacement of entire camera assemblies when a single camera fails, and lack methods to detect changes in optical components post-calibration, affecting the system's optical performance.
Innovation Solution
A comprehensive field calibration process that determines and optimizes coordinate system transforms between individual cameras and the vehicle support surface, allowing for in-field replacement of defective cameras and detection of optical component changes, thereby maintaining system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entire camera assemblies are replaced when a single camera fails, then system reliability is maintained, but device complexity and cost increase
Solution Approach 1:
The patent divides the camera assembly into independent replaceable camera units (front camera and rear camera as separate modules) that can be individually replaced without replacing the entire assembly. The calibration data is segmented and stored per-camera, enabling independent calibration of individual cameras while maintaining system-wide coordinate transformation accuracy.
Solution Approach 2:
The patent implements dynamic calibration parameters that can be updated for individual cameras after replacement. The system stores and updates per-camera calibration data (intrinsic parameters, extrinsic parameters, distortion coefficients) independently, allowing the replaced camera to be recalibrated and integrated back into the system without affecting other cameras.
2Manufacturing precision
If traditional factory calibration is used, then manufacturing precision is established, but ease of repair deteriorates
Solution Approach 1:
The patent performs comprehensive calibration and establishes coordinate transformation relationships between all cameras during factory assembly. This preliminary calibration data is stored in the system, enabling rapid field repair by simply replacing the defective camera and loading its pre-calibrated parameters, without requiring complex field calibration procedures.
Solution Approach 2:
The patent creates and stores digital copies of calibration data (intrinsic parameters, extrinsic parameters, distortion coefficients) for each camera. When a camera is replaced, these copied calibration parameters are loaded into the new camera, instantly restoring the calibrated state without requiring physical recalibration in the field.
3Measurement precision
If comprehensive calibration data is stored for all cameras, then measurement precision is improved, but loss of information increases
Solution Approach 1:
The patent extracts and stores only the essential calibration parameters needed for coordinate transformation (intrinsic parameters, extrinsic parameters, distortion coefficients) for each camera. By identifying and storing only these critical parameters rather than complete calibration datasets, the system maintains measurement precision while minimizing data storage requirements.
Data Source
AI summary
A process for calibrating and evaluating a machine-vision vehicle wheel alignment system having front and rear imaging components associated with each of the left and right sides of a vehicle support structure. Each pair of imaging components defines a front and rear field of view, with a common overlapping region associated with each respective side of the vehicle support structure. Optical targets disposed within each of the overlapping field of view regions are observed by the imaging components to establish performance ratings for the system as a whole, for groups of components within the system, and for individual components within the system.