This course teaches advanced principles for endowing mobile autonomous robots with capabilities to autonomously learn new skills and to physically interact with the environment and with humans. It also provides an overview of different robot system architectures. 

Topics Include

• Reinforcement Learning and its relationship to optimal control
• Contact and dynamics models for prehensile and non-prehensile robot manipulation,
• Imitation learning and human intent inference
• Different system architectures and their verification

You will learn the theoretical foundations for these concepts and implement them on simulated mobile manipulation platforms. In homework, the Robot Operating System (ROS) will be used extensively for demonstrations and hands-on activities.

Please note that this course is cross listed with AA274B.

What You Need to Succeed

• A conferred bachelor’s degree with an undergraduate GPA of 3.0 or better
• Basic programming (e.g., CS106A)
• Linear algebra (e.g., MATH51 or CME 100)
• Probability theory (e.g., CS109 or STATS116) 
• Principles of Robot Autonomy I (AA274A) or equivalents

What You Need To Get Started

Before enrolling in your first graduate course, you must complete an online application.

Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.

Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your mystanfordconnection account at any time.

Learn more about the graduate application process.

How Much It Will Cost

Learn more about tuition and fees.