This course will cover basic principles for endowing mobile autonomous robots with perception, planning, and decision-making capabilities. Algorithmic approaches for robot perception, localization, and simultaneous localization and mapping; control of non-linear systems, learning-based control, and robot motion planning; introduction to methodologies for reasoning under uncertainty, e.g., (partially observable) Markov decision processes. Extensive use of the Robot Operating System (ROS) for demonstrations and hands-on activities. Prerequisites: CS 106A or equivalent, CME 100 or equivalent (for linear algebra), and CME 106 or equivalent (for probability theory).
Lectures meet on Tuesdays and Thursdays from 10:30am to 11:50am, Fridays from 10:00am to 11:20am. They will all be online. Friday lectures are optional for those enrolled in AA 174A. For all others, the homework will require material taught during the Friday lectures.
Sections are on Mondays and Wednesdays from 10:30am to 12:30pm, Mondays from 3:00pm to 5:00pm, Tuesdays from 4:00pm to 6:00pm, and Thursdays from 2:00pm to 4:00pm. They will all be online.
Prof. Pavone's office hours are on Tuesdays 1:00pm to 2:00pm and by appointment, all online.
CA office hours are on Tuesdays from 2:00pm to 4:00pm and Thursdays from 4:00pm to 6:00pm, all online.