This course will cover basic principles for endowing mobile autonomous robots with planning, perception, and decision-making capabilities. Algorithmic approaches for trajectory optimization; robot motion planning; robot perception, localization, and simultaneous localization and mapping (SLAM); state machines. Extensive use of the Robot Operating System (ROS) for demonstrations and hands-on activities. Prerequisites: CS 106A or equivalent, CME 100 or equivalent (for calculus, linear algebra), and CME 106 or equivalent (for probability theory).
Mac Schwager |
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Roya Firoozi |
Javier Yu | Tanmay Agarwal | Keiko Nagami | MacVincent Agha-Oko |
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Abhyudit Manhas | Joe Vincent | Sunny Singh |
Lectures meet on Tuesdays and Thursdays from 1:30pm to 2:50pm at Gates B1.
Students are expected to attend one 2-hour section each week. Check announcements for more details
Mac's office hours are Tuesdays 3-4 PM in Durand 266 and by appointment.
Monday (Hybrid, 5:30 PM-7:30 PM, Durand 023) Sunny & Tanmay
Tuesday (Hybrid, 10 AM-12 PM, Durand 450) Joe & Tanmay
Wednesday (Hybrid, 9 AM-11 AM, Durand 270) Keiko & Javier
Thursday (In-Person, 6:30 PM-8:30 PM, Skilling) Abhyudit & MacVincent
For urgent questions, email the staff mailing list at aa274a-aut2324-staff@lists.stanford.eduThe class syllabus is on Canvas.
You may need to use VMWare to run various parts of the software for this class. Follow the setup guide here.
Refer to the syllabus on Canvas.
Follow this link to access the course website for the previous edition of Principle of Robot Autonomy I.