Projected Pattern Camera Calibration for Multi-Camera Workcells
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Solution Overview
Problem
Existing robotic vision systems face challenges in accurately calibrating multiple cameras in a workcell environment, requiring manual intervention and specialized calibration targets, which can be costly and disrupt production, especially in complex industrial settings with varying lighting and geometry.
Innovation Solution
An automated system that projects a pattern into the environment using a projector, captures images from multiple cameras, and computes calibration parameters, including intrinsic, extrinsic parameters, and camera-to-camera transforms, without the need for physical targets, allowing real-time recalibration and drift correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration with physical targets is used, then calibration accuracy can be achieved, but production downtime increases and operational complexity increases
Solution Approach 1:
The patent replaces physical calibration targets and manual mechanical adjustment processes with an automated optical projection system. A projector displays calibration patterns that are captured by cameras, and a computing system automatically calculates calibration parameters, eliminating the need for manual intervention with physical targets while maintaining calibration accuracy.
Solution Approach 2:
The calibration system performs self-calibration automatically without requiring external manual intervention. The computing system processes images from multiple cameras, identifies geometric features, and computes calibration parameters autonomously, allowing the system to recalibrate during production without stopping operations.
2Measurement precision
If specialized calibration targets are used, then calibration precision improves, but system complexity and cost increase
Solution Approach 1:
Instead of using specialized physical calibration targets, the system projects digital calibration patterns onto the workcell environment. These projected patterns serve as virtual copies of calibration targets, eliminating the need for expensive physical targets while maintaining the geometric features necessary for accurate calibration.
Solution Approach 2:
The projection system can display various calibration patterns and can be used for multiple calibration scenarios without requiring different physical targets. The same projector and camera system can calibrate different camera configurations by simply changing the projected pattern, reducing overall system complexity.
3Measurement precision
If multiple cameras are calibrated manually, then calibration accuracy is maintained, but operational efficiency decreases
Solution Approach 1:
The system performs preliminary capture of calibration images from all cameras simultaneously, then processes all calibration data together to compute calibration parameters for multiple cameras in one automated operation. This eliminates the need for sequential manual calibration of each camera while maintaining accuracy.
Solution Approach 2:
The patent combines the calibration process for multiple cameras into a single automated workflow. The computing system processes images from all cameras, identifies geometric features across all views, and computes calibration parameters for the entire camera system simultaneously, dramatically improving operational efficiency compared to manual calibration of each camera separately.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for computing one or more calibration parameters using a projected pattern. In one aspect, a method comprises projecting a pattern having a plurality of shapes in an environment using a projector, capturing images of the pattern from at least two different cameras, determining one or more geometric features of shapes in the captured images and correspondences between the geometric features for a pairing of cameras in the at least two different cameras, and computing one or more calibration parameters for the pairing of cameras according to the correspondences between the geometric features in the captured images.