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AI Image Processing for Robot Part Control by International Journal of Innovative Science and Research Technology is a document available to read on EtoBox.
This study presents an AI-assisted image processing system designed to enhance part feeding control in industrial robot cells, utilizing the YOLOv7-tiny model for accurate part detection and quality control. The system achieved a 98.07% accuracy rate with 2400 data samples and aims to minimize human errors in part placement, thereby improving production efficiency. The implementation includes hardware components like an NVIDIA JETSON AGX ORIN and a BASLER camera, alongside PLC communication for real-time mo
- Author
- International Journal of Innovative Science and Research Technology
- Language
- EN