Robot Hand-Eye Calibration Using Axis-Wise Error Convergence
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current hand-eye calibration methods for robot arms require human intervention and are often unsatisfactory due to operator error, leading to inaccurate coordinate transformation relationships between the robot arm, camera, and target object.
Innovation Solution
A hand-eye calibration method and device that automatically calibrate the coordinate transformation relationships by sequentially updating mapping relationships between the robot arm, camera, and tool set in each dimension based on a scale, minimizing errors and reducing computational complexity through convergence along one axis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual hand-eye calibration is performed by user, then coordinate transformation relationship can be calibrated, but calibration accuracy deteriorates due to operator error and insufficient professional background
Solution Approach 1:
The system performs self-calibration by automatically capturing images at multiple positions, computing transformation matrices, and iteratively optimizing calibration parameters without requiring manual intervention. The robot arm autonomously moves to predetermined positions and the system automatically processes the captured images to refine the coordinate transformation relationships.
Solution Approach 2:
The manual mechanical calibration process is replaced with an automated computational system that uses image processing algorithms and mathematical optimization to determine transformation matrices. The system substitutes human operators with automated image capture and computational analysis to achieve higher calibration precision.
2Measurement precision
If comprehensive hand-eye calibration is performed, then calibration accuracy is improved, but calibration time increases significantly
Solution Approach 1:
The system pre-determines multiple calibration positions and plans the calibration sequence in advance. By preparing the calibration path and parameters beforehand, the system avoids time-consuming trial-and-error adjustments during the actual calibration process, thereby reducing total calibration time while maintaining accuracy.
Solution Approach 2:
The calibration process continuously captures images and updates transformation matrices without interruption. The robot arm moves smoothly between predetermined positions and the system continuously processes image data to refine calibration parameters, eliminating idle time and maintaining continuous productive action throughout calibration.
3Measurement precision
If detailed calibration in each dimension is performed, then transformation matrix accuracy is improved, but computational complexity increases
Solution Approach 1:
The calibration process segments the three-dimensional calibration space into multiple one-dimensional lines along each axis. The system performs calibration sequentially along each dimension by moving the robot arm to predetermined positions on calibration lines, breaking down the complex 3D calibration problem into simpler 1D sub-problems that are computationally more efficient to solve.
Solution Approach 2:
The system transforms the complex multi-dimensional calibration problem into a series of one-dimensional calibration tasks by projecting the calibration onto calibration lines along each axis. This dimensional reduction simplifies the computational burden while maintaining the accuracy of the full three-dimensional transformation matrix calibration.
Data Source
AI summary
A hand-eye calibration method and a hand-eye calibration device for a robot arm are provided. The method includes following steps. A first mapping relationship between a base of the robot arm and a terminal of the robot arm and a second mapping relationship between a camera and a target object are obtained. Based on a scale, a third mapping relationship between the terminal of the robot arm and a tool set mounted on the terminal and a fourth mapping relationship between the camera and the base in each dimension are updated to minimize an error between a position of the target object in an image captured by the camera and a position of the tool set. In response to the error being convergent and the scale being less than or equal to a scale threshold, the third mapping relationship and the fourth mapping relationship calibrated by the scale are output.