Autonomous Systems Engineering: The Intersection of Robotics and AI

Autonomous systems engineering represents a confluence of robotics and artificial intelligence (AI), aiming to create machines capable of performing tasks with minimal human intervention. With AI algorithms and robotic hardware advancements, autonomous systems have revolutionised the manufacturing and healthcare industries. This paper explores the intersection of robotics and AI, examining how autonomous systems are engineered, their applications, and their challenges. The methodologies employed in designing and developing these systems are analysed, including machine learning, reinforcement learning, sensor integration, and real-time decision-making. Various case studies illustrate these technologies' practical implementation, such as autonomous vehicles, industrial robots, and drones. The results show that AI-driven robotics is transforming industries, optimising productivity, and enhancing precision, though issues like system safety, ethical concerns, and computational limitations remain challenges. The conclusion emphasises the need for continuous research to overcome these barriers and ensure the' safe and efficient deployment of autonomous systems in diverse environments.