Robot-Camera Calibration Using Criterion Point Image Centering
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Solution Overview
Problem
Existing methods for calibrating robot systems with attached cameras are inefficient and prone to inaccuracies, particularly in setting the offset of tools relative to the arm, which requires precise manipulation of the arm to align with a criterion point.
Innovation Solution
A calibration method that involves moving a robot to achieve specific states to align a criterion point within an image captured by a camera, using a combination of translations and rotations to derive the position of the criterion point and perform calibration between the robot and camera coordinate systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual manipulation method is used to align tool with criterion point, then calibration accuracy can be achieved, but calibration time is prolonged
Solution Approach 1:
The patent replaces manual mechanical manipulation with an automated vision-based system. The camera captures images of the criterion point, and image processing algorithms automatically calculate the criterion point's position and the tool's offset, eliminating the need for operators to manually manipulate the arm while visually identifying boundary conditions.
Solution Approach 2:
The system performs self-calibration by using the camera to automatically detect the criterion point position and compute the tool offset without requiring external manual intervention. The robot arm moves to predetermined positions, and the system autonomously processes the image data to derive calibration parameters.
2Measurement precision
If multiple robots are calibrated using manual method, then each robot can be accurately set, but total calibration time increases significantly
Solution Approach 1:
The automated vision system enables rapid calibration by replacing slow manual manipulation with fast image capture and digital processing. Each robot can be calibrated quickly and accurately, significantly increasing the throughput when calibrating multiple robots.
Solution Approach 2:
The system uses predetermined positions and predetermined surfaces that are prepared in advance. The criterion point is pre-positioned on a predetermined surface, and the robot arm moves to pre-defined positions, allowing for efficient and rapid calibration without requiring complex real-time adjustments.
3Ease of operation
If visual identification method is used to determine touch state, then operator can control arm movement, but identification accuracy deteriorates
Solution Approach 1:
The patent replaces visual identification with optical measurement. The camera captures precise images of the criterion point, and image processing algorithms accurately determine the criterion point's position and the touch state, eliminating the limitations of human visual identification while maintaining ease of operation.
Data Source
AI summary
A method form performing calibration between a robot and a camera includes achieving a first state in which a criterion point of an image is captured with the camera, achieving a second state in which the camera is rotated by a first angle of rotation around a first imaginary axis passing through a control point at the arm, achieving a third state in which the criterion point is located at the center of the image captured with the camera, achieving a fourth state in which the camera is rotated by a second angle of rotation around a second imaginary axis passing through a reference point, achieving a fifth state in which that criterion point is located at the center of the image captured with the camera, and performing the calibration between the robot and the camera.