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Selective Object Detection and OCR-Based Sorting in Semiconductor Pick-and-Place Robotics
Conference proceeding

Selective Object Detection and OCR-Based Sorting in Semiconductor Pick-and-Place Robotics

Daniel Walczak, Lucas Linnemann, Cheol-Hong Min and Hassan Salamy
2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET), pp.1-6
07/03/2025

Abstract

AI accelerators Antennas Convolutional Neural Networks (CNNs) Feeds Filtering Filters Integrated circuits Microprocessor chips Millimeter wave integrated circuits MIMICs Monolithic integrated circuits Object Detection Optical Character Recognition (OCR) Pick-and-Place
This paper presents an automated system for semiconductor chip recognition, classification, and pick-and-place operations using a custom object detection model, optical character recognition (OCR), and robotic kinematics. The Hailo AI processor, integrated with a Raspberry Pi, performs recognition, while classification is handled by EasyOCR. A dynamic detection pipeline accommodates varying chip attributes, including pin count, size, and labeling. The process includes image preprocessing, bounding box extraction, and robotic actuation. Experimental testing yielded a 97.9% classification accuracy, demonstrating the system's adaptability, speed, and precision for real-time sorting in smart manufacturing environments.

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