Vehicle Camera Calibration with Infrastructure-Based Offset Correction
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Solution Overview
Problem
Existing vehicle camera calibration systems at end-of-line stations are inefficient due to labor, time, and infrastructure requirements, and fail to account for dynamic conditions that affect accuracy, such as lighting and off-axis maneuvers.
Innovation Solution
A method and system for calibrating onboard image sensors using infrastructure and onboard data to generate an offset matrix, adjusting the rotation matrix dynamically based on infrastructure-based and image-based positional characteristics, and employing recursive updating routines to improve accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated camera calibration EOL station with fiducial marker is used, then calibration accuracy can be maintained under controlled conditions, but labor requirements, time consumption, and infrastructure resources increase significantly
Solution Approach 1:
The vehicle itself serves as the calibration platform by utilizing its own onboard sensors (lidar, radar, ultrasonic sensors) to detect environmental features and perform self-calibration of the camera system, eliminating the need for external dedicated calibration equipment and personnel
Solution Approach 2:
The onboard sensor suite originally designed for navigation and obstacle detection is repurposed to perform camera calibration functions, allowing the same sensors to serve multiple functions: navigation, obstacle avoidance, and calibration
2Device complexity
If a static fiducial marker calibration method is used, then calibration setup is simplified, but dynamic conditions such as lighting changes, off-axis maneuvers, and signal noise are not accounted for, reducing calibration accuracy
Solution Approach 1:
The calibration system transitions from static fiducial marker detection to dynamic environmental feature detection, where the vehicle moves through the environment and uses multiple sensors to capture and process changing spatial relationships, allowing calibration under varying lighting and angular conditions
Solution Approach 2:
The system uses feedback from multiple onboard sensors (lidar, radar, ultrasonic) to continuously monitor and adjust calibration parameters based on detected environmental features, compensating for dynamic conditions such as lighting changes and off-axis maneuvers
Data Source
AI summary
A method includes obtaining infrastructure data from one or more infrastructure sensors, determining an infrastructure-based positional characteristic of the vehicle based on the infrastructure data, obtaining onboard image data from the onboard image sensor, determining an image-based positional characteristic of the vehicle based on the onboard image data and a digital twin of the manufacturing environment, generating an offset matrix based on the infrastructure-based positional characteristic and the image-based positional characteristic, and selectively adjusting a rotation matrix of the onboard image sensor based on the offset matrix and one or more additional offset matrices.