Robot-Camera Calibration Using Marker-Centered Rotational Alignment
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Solution Overview
Problem
Existing robot calibration methods are inefficient and inaccurate, particularly when setting tool offsets relative to the arm, as operators struggle to precisely manipulate the arm to touch a criterion point, leading to prolonged calibration times, especially with multiple robots.
Innovation Solution
A calibration method that involves a series of robotic states and camera rotations to derive the position of a criterion point, allowing for automatic calibration between the robot and camera coordinate systems, using translational and rotational movements to align the camera and tool, enabling accurate coordinate system alignment without operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual manipulation method is used to teach criterion point position, then calibration accuracy can be achieved, but calibration time is prolonged
Solution Approach 1:
The robot performs calibration operations autonomously using vision guidance. The camera captures marker positions and the robot automatically adjusts its movements to achieve precise alignment, eliminating the need for manual operator intervention while maintaining high positioning accuracy through automated feedback control.
Solution Approach 2:
Manual mechanical manipulation of the robot arm is replaced with automated vision-based positioning. The camera system detects marker coordinates and the control unit calculates required movements, substituting human operator actions with an automated optical-mechanical system that achieves both speed and precision.
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:
Each robot is equipped with an integrated camera and control system that enables autonomous calibration. The robot independently performs marker detection, position calculation, and adjustment operations, allowing multiple robots to be calibrated simultaneously or in rapid succession without requiring operator attention for each individual calibration process.
Solution Approach 2:
The calibration system uses a standardized marker and automated vision-based approach that can be applied universally to multiple robots. The same camera-based methodology and control algorithms work across different robot units, enabling consistent accurate calibration while maintaining high throughput through process standardization and automation.
3Measurement precision
If complex manipulation is required to touch criterion point, then positioning accuracy can be achieved, but operation difficulty increases
Solution Approach 1:
Complex manual arm manipulation is replaced with automated vision-guided positioning. The camera captures the marker position and the control unit automatically calculates the precise movements needed, substituting difficult manual coordination tasks with an automated system that handles the complexity of multi-axis coordination and positioning calculations.
Solution Approach 2:
The camera and control unit act as intermediaries between the operator's simple command to calibrate and the complex multi-axis robot movements required for precise alignment. The vision system detects marker coordinates and the control system translates this into appropriate joint movements, mediating the complexity and presenting a simple interface to the operator.
Data Source
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AI summary
A method for performing calibration between a robot coordinate system and a camera coordinate system includes achieving a first state in which a criterion point at a predetermined surface is located at the center of an image captured with a camera, achieving a second state in which the camera is rotated by a first angle of rotation around a first imaginary axis perpendicular to the predetermined surface and 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, deriving a reference point that is a provisional position of the criterion point based on information on the first and third states and the first angle of rotation, achieving a fourth state in which the camera is rotated by a second angle of rotation around a second imaginary axis perpendicular to the predetermined surface and passing through the reference point, achieving a fifth state in which the criterion point is located at the center of the image captured with the camera, deriving the position of the criterion point from the information on the first and fifth states and the first and second angles of rotation, or the information on the third and fifth states and the second angle of rotation, and performing the calibration between the robot coordinate system and the camera coordinate system based on the derived position of the criterion point.