This applications-focused course surveys the current usage and trends in robotics and human-augmenting systems, including autonomous systems, with applications in manufacturing, human services, autonomous vehicles, and facial recognition. It covers foundational mechanical concepts like kinematics, dynamics, sensors, and actuators, and advances to computer vision, object detection, recognition, and reinforcement learning (MDPs, rewards, policies). Students will explore tools like OpenCV, TensorFlow, and PyTorch, along with strategies for risk mitigation in autonomous systems. The course also addresses safety concerns, ethical and legal issues, and examines trends, legislation, and regulations shaping the field. Pre-requisites: Standard admission requirements.