The rise of autonomous technologies has led to machines capable of perception, reasoning, and decision-making without human intervention. Embedded intelligence combines sensors, processors, and algorithms to achieve real-time adaptability. Autonomous Systems and Embedded Intelligence examines the architecture, control strategies, and AI integration within autonomous machines. It covers perception systems, sensor fusion, path planning, and machine learning applications. The book also discusses ethical and safety challenges in robotics and self-driving systems. Through real-world examples, it connects theoretical foundations with practical design approaches, serving as an essential guide for robotics engineers and automation researchers.