Düşük Maliyetli Robotik Kol Aracılığıyla Üretken Yapay Zeka Görüntülerinin Çizilmesi

This study proposes an AI-driven system that integrates generative artificial intelligence with robotic arm to create and physically render visual content. Utilizing state-of-the-art text-to-image models, the system first generates high-resolution images based on natural language prompts. These images are then processed and translated into vector paths suitable for robotic execution. A robotic arm, specifically the BrachioGraph platform, is employed to draw the generated content on a physical medium, effectively bridging the gap between digital generation and tangible realization. The system architecture combines deep learning-based image synthesis, path optimization algorithms, and precise robotic control. Although the study has certain optimization errors that cause vibration because it was created with Raspberry Pi and simple equipments, it is a prototype study that shows that artistic studies can be created by AI technologies.This interdisciplinary approach demonstrates a novel pipeline where AI-generated creativity is physically manifested through robotics, opening new possibilities in automated content creation, human-machine collaboration, and AI-driven artistic expression.