Optical Robotic Sorting Apparatus for Corn Defect Detection
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Solution Overview
Problem
Current methods for sorting ears of corn rely heavily on human labor, which is inefficient, costly, and prone to inconsistencies, and existing automated systems have not effectively replaced human sorting capabilities, particularly in identifying and separating defective corn.
Innovation Solution
An optical robotic sorting method and apparatus that uses a light source, imaging device, and robotic arm to identify and sort defective ears of corn by illuminating, imaging, analyzing, and removing them from a conveyor using a central processing unit and vacuum tool.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human labor is used to sort ears of corn on a conveyor, then the sorting can be performed with simple equipment, but the productivity is low and costs are high due to the need for multiple people and frequent breaks
Solution Approach 1:
The patent replaces the mechanical human sorting system with an automated optical sorting system. Cameras capture images of ears of corn on the conveyor, image processing software analyzes the images to identify defective corn, and robotic arms or air jets physically remove the defective items. This substitution eliminates the need for multiple human workers while maintaining high sorting throughput.
Solution Approach 2:
The sorting system performs self-inspection and self-correction through automated image analysis. The system independently identifies defective corn based on visual criteria programmed into the software, without requiring human intervention for each item. This autonomous operation enables continuous high-speed sorting without breaks or training requirements.
2Measurement precision
If multiple people are deployed to sort corn accurately, then the sorting accuracy improves, but the loss of time increases due to coordination and breaks
Solution Approach 1:
The automated optical sorting system operates continuously without interruption. The conveyor belt moves ears of corn past the cameras at constant speed, and the image processing and robotic removal occur in real-time. This continuous operation eliminates the breaks and coordination delays inherent in human-based sorting while maintaining consistent accuracy through programmed detection criteria.
Solution Approach 2:
The system performs preliminary detection and classification of defective corn through image capture and analysis before physical removal is needed. The software pre-identifies all defective items in a batch before the robotic arms or air jets execute the removal sequence, optimizing the timing and reducing overall cycle time.
3Ease of operation
If human workers are used for sorting, then the system is easy to operate, but the reliability decreases due to inconsistency and inability to repeat processes the same way every time
Solution Approach 1:
The system maintains reliability through consistent application of detection parameters programmed into the image processing software. Criteria such as color thresholds, size ranges, and defect patterns are defined as fixed parameters that are applied uniformly to every ear of corn. This parameter-based approach eliminates the variability inherent in human judgment while keeping the system easy to operate through centralized software control.
Solution Approach 2:
The system incorporates feedback mechanisms where the image processing results are immediately fed to the robotic removal system. The closed-loop control ensures that detected defective corn is consistently and reliably removed. Additionally, the system can log and review sorting decisions, allowing for verification and adjustment of detection parameters to maintain high reliability over time.
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
The system reduces reliance on human labor, increases sorting efficiency and accuracy, and decreases costs by effectively identifying and sorting defective corn into appropriate areas, improving the overall processing efficiency.
Implementation Method 1
illuminating the ear corn using at least one light source
Implementation Method 2
a vacuum tool connected to the robotic arm, a vacuum source operably connected to the vacuum tool
Data Source
AI summary
An optical robotic sorting apparatus for identifying and sorting a product is provided. In the preferred embodiment, the optical robotic sorting apparatus illuminates the product with a light source, images the product using at least one imaging device, analyzes the image, and activates a robotic sorter to sort the product; wherein the robotic sorter utilizes a vacuum tool to handle the product.