Robotic systems are quickly becoming more capable and adaptable, entering new domains from transportation to healthcare. To reliably carry out complex tasks in changing environments and around people, these systems rely on increasingly sophisticated artificial intelligence. This course covers the core concepts and techniques underpinning modern robot autonomy, including planning under uncertainty, imitation and reinforcement learning, multiagent interaction, and safety. The lab component introduces the Robot Operating System (ROS) framework and applies the learned theory to hands-on autonomous driving assignments on 1/16-scale robot trucks.