Robot Hand-Eye Calibration Using Force-Sensed Contact Marks
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Solution Overview
Problem
Current hand-eye calibration methods for robots are manual, complex, and prone to low accuracy due to human error, requiring precise movement and calibration of a robot arm to a calibration target, which is time-consuming and affected by the accuracy of the calibration needle and camera alignment.
Innovation Solution
The introduction of a force sensor on the robot arm allows for automatic hand-eye calibration by detecting contact with a calibration target and recording coordinates, enabling the calculation of a calibration transformation matrix without human operation, and includes a parallelization correcting step to ensure the camera's imaging plane is parallel to the target, improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual operation is used to move the robot arm to calibration points, then the calibration process can be completed, but the calibration accuracy is greatly affected by human factors and it takes a long time
Solution Approach 1:
The system uses the robot arm itself to perform the calibration by automatically moving to predetermined positions and using its own camera to capture images, eliminating the need for manual operation and achieving self-calibration
Solution Approach 2:
The patent replaces manual mechanical operation with an automated control system that uses force sensors to detect contact with the calibration target and automatically controls the robot arm's movement and positioning
2Measurement precision
If a calibration needle is used for manual calibration, then the calibration can be performed, but the accuracy is affected by the calibration needle accuracy and manual precision
Solution Approach 1:
The patent extracts and removes the calibration needle from the system, replacing it with a force sensor that detects contact with the calibration target through force feedback, thereby eliminating the accuracy limitations of the calibration needle
Solution Approach 2:
The force sensor serves multiple functions: detecting contact with the calibration target, determining contact positions, and providing feedback for automatic positioning, replacing the single-function calibration needle
3Measurement precision
If the camera imaging plane is not parallel to the calibration target, then the calibration can proceed, but the calibration accuracy is affected
Solution Approach 1:
The force sensor provides real-time force feedback during the calibration process, enabling the system to detect and correct alignment deviations between the camera imaging plane and the calibration target, ensuring parallel alignment for accurate calibration
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enhances calibration efficiency and accuracy by automating the process, reducing human error and ensuring precise alignment, thereby improving the overall performance of robot vision-guided tasks.
Implementation Method 1
when a force sensor on the robot arm detects that a force of the end of the calibration apparatus in contact with the calibration target reaches a preset force
Data Source
AI summary
When a force sensor on a robot arm detects that the force of contact between an end of a calibration device and a calibration plate reaches a threshold, the robot arm stops, and the end of the calibration device performs marking at the contact position between the end of the calibration device and the calibration plate. The robot arm moves upward and stops at a position where the end of the robot arm is at a predetermined height. At this position, a camera at the end of the robot arm photographs marks on the calibration plate, records the coordinates of the marks in the camera coordinate system, and records the coordinates of the end of the calibration device in the robot coordinate system. A calibration transformation matrix is calculated according to the recorded coordinates of at least three marks.