Autonomous systems are revolutionizing industries and daily life by integrating robotics, control systems, and embedded intelligence. This study explores their evolution and key components, covering robotics fundamentals like kinematics, dynamics, sensors, actuators, and motion planning. Control systems are analyzed with focus on feedback, adaptive techniques, and distributed architectures for precision and stability. Embedded intelligence, powered by machine learning, real-time decision-making, and edge computing, is highlighted as a driver of smart, responsive systems. Communication technologies, including V2X protocols and data security, are discussed for ensuring reliable connectivity. System design complexities-spanning hardware-software integration, verification, and testing-are examined to address scalability and robustness. Applications in autonomous vehicles, drones, healthcare robotics, industrial automation, and smart cities demonstrate their transformative impact. Ethical challenges, scalability, and emerging trends are explored alongside real-world case studies, making this a vital resource for advancing autonomous systems.