Through-Beam Sensor Auto-Teaching for Precise Robot Pin Location
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Solution Overview
Problem
Manual teaching of robot locations in manufacturing environments is time-consuming and prone to human error, particularly in precise applications like semiconductor wafer handling, where accurate movement is crucial to prevent damage to workpieces and equipment.
Innovation Solution
An automated method using a through-beam sensor with a light emitter and receiver on an articulated robot's end effector to sense pins at different distances and orientations, allowing for precise determination of pin locations within the robot's coordinate system through sensing operations and regression analysis to improve teaching accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual teaching method is used to teach robot locations, then the robot can be taught positions and orientations, but the process is time-consuming and prone to human error
Solution Approach 1:
The patent replaces manual mechanical teaching operations with an automated optical sensing system. A through-beam sensor mounted on the robot end effector automatically detects pin locations and orientations, eliminating the need for manual measurement and data entry. This substitution of mechanical/manual processes with automated sensing directly reduces teaching time while improving accuracy through consistent, error-free data collection
Solution Approach 2:
The robot performs self-teaching by autonomously moving the through-beam sensor to detect pin locations and orientations without human intervention. The system automatically collects position and orientation data, processes it through regression analysis, and updates its coordinate system transformations independently. This self-service capability eliminates dependency on manual teaching operations, significantly reducing teaching time while maintaining high precision through automated feedback loops
2Reliability
If manual teaching is used, then the robot can learn workpiece locations, but human error may cause inaccurate positioning
Solution Approach 1:
The patent replaces manual teaching operations with automated optical sensing and computational processing. The through-beam sensor systematically measures pin locations and orientations, while regression analysis algorithms automatically process the data to determine accurate coordinate transformations. This eliminates human error in data collection and processing, significantly improving positioning reliability
Solution Approach 2:
The system implements continuous feedback through the through-beam sensor that automatically detects pin positions and orientations. The sensor data feeds into regression analysis that refines the coordinate system transformations, creating a closed-loop feedback mechanism. This automated feedback eliminates human error while maintaining ease of operation, as the system self-corrects and optimizes positioning accuracy without requiring manual intervention
3Extent of automation
If through-beam sensor is used for sensing operations, then the robot can autonomously determine pin locations, but the device complexity increases
Solution Approach 1:
The through-beam sensor serves multiple functions: it detects pin locations, determines pin orientations, and provides data for regression analysis. By mounting the sensor on the robot end effector, it becomes part of the robot's existing coordinate system framework, allowing a single device to perform multiple teaching functions. This multi-functionality increases automation capability while minimizing the addition of separate complex subsystems
Solution Approach 2:
The patent merges the sensing function with the robot's existing end effector structure. The through-beam sensor is integrated into the end effector, combining measurement capabilities with the robot's manipulator. This merging approach allows autonomous teaching capability to be achieved by integrating sensing into existing hardware rather than adding separate complex sensing systems, thereby increasing automation while controlling device complexity
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
Enables accurate placement of workpieces within a few millimeters, reducing human error and increasing efficiency by allowing the robot to autonomously determine and adjust to changes in its environment, such as thermal expansion, ensuring precise and safe movement of wafers during manufacturing.
Implementation Method 1
The through-beam sensor includes a light emitter provided on one of the first protruding member and the second protruding member. The through-beam sensor further includes a light receiver provided on an other of the first protruding member and the second protruding member. The through-beam sensor is configured to sense when an object is present between the light emitter and the light receiver.
Data Source
AI summary
A method of teaching a robot including providing a pin at a location within a work station, and the robot in an area adjacent to the station. The robot having an arm and an end effector that pivots. The end effector has a through-beam sensor including a light emitter and a light receiver to sense when an object is present therebetween. The robot is moved to perform sensing operations in which the sensor senses the pin, such operations are performed while a position and/or an orientation of the end effector are varied to gather sensed position and orientation data. The sensing operations are performed such that the pin is located at different distances between the emitter and the receiver as the robot moves the sensor across the pin. Calculations are performed on the data to determine the location of the pin with respect to a coordinate system of the robot.