Robot Hand-Eye Calibration Using Gridded Workspace Points
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The calibration process for robots is cumbersome and inefficient due to the need for manual participation and high professional quality, especially when collecting calibration data from multiple positions, which affects the accuracy of the robot's ability to move to the destination for operations.
Innovation Solution
A method for robot calibration that involves obtaining operation space information, gridding the space to determine operation space points, controlling the execution end to collect calibration data at preset requirements, and calibrating the hand and image detection device using a computer-implemented method, simplifying the process and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual participation is used to collect calibration data from multiple positions, then calibration accuracy is improved, but calibration complexity and time consumption increase
Solution Approach 1:
The calibration system performs self-calibration through automated coordinate system transformation between the image detection device and execution end. The robot controls its own calibration process by automatically moving to predetermined positions and collecting calibration data without requiring manual intervention, thereby maintaining high calibration accuracy while eliminating operational complexity
Solution Approach 2:
The system pre-establishes a correspondence relationship between the image detection device coordinate system and the execution end coordinate system before actual calibration begins. Predetermined positions are pre-calculated and prepared, allowing the calibration process to proceed automatically without real-time manual guidance, thus improving efficiency while maintaining precision
2Measurement precision
If manual participation is required for calibration data collection, then calibration accuracy is maintained, but productivity decreases
Solution Approach 1:
The manual mechanical operation of positioning and data collection is replaced with an automated control system. The robot controller automatically moves the execution end to predetermined positions and coordinates with the image detection device to collect calibration data, substituting human-operated mechanical processes with automated electro-mechanical systems, thereby dramatically improving calibration efficiency while maintaining accuracy
Solution Approach 2:
A coordinate transformation module serves as an intermediary between the image detection device and the execution end. This module automatically calculates and transforms coordinates between different reference frames, eliminating the need for manual coordinate mapping while ensuring precise calibration accuracy, thus resolving the conflict between efficiency and precision
3Manufacturing precision
If calibration data is collected from multiple positions, then robot movement precision is improved, but calibration time increases
Solution Approach 1:
The system pre-calculates and stores a set of predetermined positions that are optimal for calibration before the actual calibration process begins. These positions are determined in advance based on the robot's workspace and the image detection device's field of view, allowing the calibration to proceed efficiently through automated movement to these pre-planned positions, thus collecting sufficient data for high precision while minimizing time loss
Solution Approach 2:
The calibration space is segmented into multiple predetermined positions that are strategically distributed to capture the essential geometric relationships. Rather than requiring continuous or exhaustive data collection, the space is divided into discrete calibration points that, when combined, provide sufficient information for accurate hand-eye calibration, reducing overall calibration time while maintaining robot movement precision
Data Source
AI summary
A robot calibration method, a robot, and a computer-readable storage medium are provided. The method includes: obtaining operation space information of the execution end of the robot; obtaining operation space points after gridding an operation space of the robot by gridding the operation space based on the operation space information; obtaining calibration data by controlling the execution end to move to the operation space points meeting a preset requirement; and calibrating the hand and the image detection device of the robot based on the obtained calibration data. In this manner, the operation space points are determined by gridding the operation space based on the operation space information, and the execution end can be automatically controlled to move to the operation space points that meet the preset requirements so as to obtain the calibration data in an automatic and accurate manner, thereby simplifying the calibration process and improving the efficiency.