Calibrated Vision-Based Robotic System for Disk Drive Assembly
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Solution Overview
Problem
Current robotic calibration techniques in disk drive manufacturing are tedious, time-consuming, and lack the necessary accuracy for high-precision assembly, often resulting in errors and contamination due to human intervention and manual positioning methods.
Innovation Solution
A calibrated vision-based robotic system using a calibration block with optical sensors and a camera to determine the camera-to-tool offset value, allowing for precise calibration of the robotic tool's position without human intervention, enabling accurate picking and placing of components in disk drives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual calibration procedures are used with human observation, then the system can be operated with simple equipment, but the calibration accuracy and precision deteriorate
Solution Approach 1:
The patent replaces manual mechanical calibration procedures with an automated vision-based system. A camera captures images of calibration targets, and computer vision algorithms automatically calculate robot position and orientation, eliminating the need for manual observation and mechanical adjustment while significantly improving calibration precision.
Solution Approach 2:
The patent introduces calibration targets with specific visual patterns as intermediaries between the robot and the camera. These targets serve as reference objects that the vision system can accurately detect and measure, enabling precise calibration without direct human intervention.
2Device complexity
If manual calibration procedures are used, then the equipment complexity remains low, but the calibration time and productivity deteriorate
Solution Approach 1:
The patent replaces time-consuming manual calibration operations with automated image capture and processing. The camera quickly captures calibration target positions, and software algorithms automatically compute transformation matrices, dramatically reducing calibration time while maintaining manageable system complexity.
Solution Approach 2:
The patent uses visual copies (images) of calibration targets captured by the camera to determine robot position and orientation. Instead of physical measurement and calculation, the system works with digital image data, enabling rapid automated calibration without complex mechanical measurement devices.
3Extent of automation
If manual calibration is performed by operators, then the system requires minimal automation, but human error and contamination risk increase
Solution Approach 1:
The patent replaces manual calibration operations with automated vision-based measurement and calculation. The camera and computer vision system objectively capture and process calibration data without human intervention, eliminating operator error and contamination risks while improving calibration reliability.
Solution Approach 2:
The calibration system performs self-calibration by automatically capturing images of calibration targets, computing position and orientation data, and generating transformation matrices without requiring human operators. This self-service approach ensures consistent, reliable calibration results free from human error.
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 significantly reduces human errors, prevents contamination, and reduces manufacturing time by providing a precise and efficient calibration process for robotic systems in disk drive assembly, enhancing the overall accuracy and speed of the manufacturing process.
Implementation Method 1
Each set of optical sensors includes an optical beam transmitter to transmit an optical beam and an optical beam receiver to receive the optical beam
Implementation Method 2
commands the camera of the machine vision assembly to capture an image of each of the plurality of camera reading points
Data Source
AI summary
A method of calibrating a vision based robotic system. The method includes engaging a calibration pin with a robotic tool and moving the calibration pin to a calibration block that includes at least one set of optical sensors having an optical transmitter to transmit an optical beam and an optical receiver to receive the optical beam. Further, the transmitted optical beam includes a center point. The method further includes: moving the calibration pin to the center point of the transmitted optical beam; determining a calibration pin center position relative to the robotic tool; and commanding a machine vision assembly having a camera to capture an image of a plurality of camera reading points of the calibration block and to determine a camera center position.