Fusion of Computer Vision and Mechanical Engineering for Intelligent Robotic Control Systems

Abstract

The integration of computer vision and mechanical engineering is revolutionizing robotic control 
systems, enabling enhanced precision, adaptability, and autonomy. This paper explores how realtime image processing, deep learning, and sensor fusion are combined with advanced mechanical 
structures and control mechanisms to optimize robotic functionality. By leveraging AI-driven 
perception and adaptive actuation, robots can interact intelligently with dynamic environments, 
execute complex tasks with high accuracy, and improve efficiency across various applications. 
Key developments in motion planning, feedback control, and mechatronic systems are discussed, 
along with challenges and future research directions. This study highlights the transformative role 
of vision-guided mechanical engineering in shaping the next generation of intelligent robotic 
systems.