Düşük Maliyetli Robotik Kol Aracılığıyla Üretken Yapay Zeka Görüntülerinin Çizilmesi

Abstract

Bu çalışma, görsel içerik oluşturmak ve fiziksel olarak işlemek için üretken yapay zekayı robotik kolla birleştiren yapay zeka odaklı bir sistem önermektedir. Sistem, en son metinden görüntüye modellerini kullanarak, önce doğal dil komutlarına dayalı yüksek çözünürlüklü görüntüler oluşturur. Daha sonra bu görüntüler işlenir ve robotik yürütme için uygun vektör yollarına çevrilir. Üretilen içeriği fiziksel bir ortama çizmek için özellikle BrachioGraph platformu olan bir robotik kol kullanılır ve dijital üretim ile somut gerçekleştirme arasındaki boşluğu etkili bir şekilde kapatır. Sistem mimarisi, derin öğrenmeye dayalı görüntü sentezini, yol optimizasyon algoritmalarını ve hassas robotik kontrolü birleştirir. Çalışma, Raspberry Pi ve basit ekipmanlarla oluşturulduğu için titreşime neden olan belirli optimizasyon hatalarına sahip olsa da, yapay zeka teknolojileriyle sanatsal çalışmaların yaratılabileceğini gösteren bir prototip çalışmadır. Bu disiplinlerarası yaklaşım, yapay zeka tarafından üretilen yaratıcılığın robotik aracılığıyla fiziksel olarak tezahür ettiği, otomatik içerik oluşturma, insan-makine işbirliği ve yapay zeka odaklı sanatsal ifadede yeni olanaklar açan yeni bir akışı göstermektedir.

Keywords

• BrachioGraph
• Üretken Yapay Zeka
• Görüntü Çizimi
• İnsan-Makine Etkileşimi

Plotting of Generative AI-Images via Low-Cost Robotic Arm

Abstract

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.

Keywords

• BrachioGraph
• Generative AI
• Robotic Arm
• Image Plotting
• Human-Machine Interaction

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