Robot Hand Position Teaching Using Virtual Substrate Alignment
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Solution Overview
Problem
The existing methods for teaching robot positions are prone to errors due to operator skill limitations, especially in complex semiconductor and liquid crystal device environments, where accurate positioning is crucial for reliability.
Innovation Solution
A robot system equipped with a camera, image data acquirer, virtual substrate generator, distance calculator, and operation control unit that calculates distance information from a substrate placing portion to a teaching substrate, allowing for precise positioning without relying on operator skill, by generating a virtual substrate and aligning it with the actual substrate, and storing the hand's position as teaching data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the end effector is brought into contact with the target for position teaching, then the robot can learn the target position, but teaching errors occur due to operator skill limitations and insufficient accuracy
Solution Approach 1:
The patent replaces the mechanical contact-based teaching method with an optical measurement system. A camera captures images of the target and end effector positions, and a calculation unit computes the actual positions based on these images. This substitution eliminates the need for manual mechanical contact teaching, thereby improving both accuracy and reliability by removing operator skill dependency.
Solution Approach 2:
The patent creates visual copies (images) of the physical positions using a camera. Instead of relying on physical contact and manual recording, the system captures optical images of the target and end effector, then calculates their positions from these image copies. This copying approach enables automated, accurate position teaching without direct mechanical interaction.
2Ease of operation
If manual teaching methods are used, then the robot can be programmed, but the process depends on operator skills and produces errors
Solution Approach 1:
The system enables the robot to teach itself positions automatically. The camera captures images, the calculation unit computes positions, and the robot learns the target position without human intervention. This self-service approach maintains operational simplicity while dramatically improving position accuracy by eliminating manual teaching errors.
3Loss of information
If contact-based teaching is used, then position data can be acquired, but errors and reduced accuracy occur
Solution Approach 1:
The patent introduces an intermediary optical measurement system between the physical world and the robot's position data. The camera acts as an intermediary that captures position information optically, and the calculation unit serves as an intermediary that transforms image data into accurate position coordinates. This intermediary approach preserves position information accuracy while managing system complexity through automated processing.
Data Source
AI summary
A control device of robot includes: image data acquirer configured to acquire image data taken by camera, image data including a teaching substrate and a substrate placing portion of a hand, the teaching substrate arranged as a teaching target at substrate target position; a virtual substrate information generator configured to generate information of a virtual substrate virtually arranged at the substrate placing portion of the hand in image data of the camera; distance information calculator configured to calculate distance information from substrate placing portion to the teaching substrate based on image data of the camera; operation control unit configured to control operation of robot arm based on distance information from the substrate placing portion to the teaching substrate such that the virtual substrate coincides with the teaching substrate; and storage unit configured to store, as teaching data, position of the hand when the virtual substrate coincides with the teaching substrate.