Course Description

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).

Instructor

Marco Pavone

Course Assistants

Chris Agia	Luis Pabon	Alvin Sun

Meeting Times

Lectures meet on Tuesdays and Thursdays from 10:30am to 11:50am at Shriram 104.

Students are expected to attend one 2-hour section each week. Check announcements for more details

Prof. Pavone's office hours are on Tuesdays 1:00pm to 2:00pm in Durand 261 and by appointment.

CA office hours are Tuesdays, 2:00 - 4:00pm @ Durand 271, Thursdays, 4:00 - 6:00pm @ Durand 353.

Syllabus

The class syllabus can be found here.

Links

Canvas -- for course content, recordings, and announcements.
Gradescope -- for homework and project submissions.
Edstem -- for discussions and questions.
Section Sign-up -- sign up for a section time slot by 12 PM on Thursday, September 28^th.

Resources

The homeworks require you to set up a local ROS2 environment and install vairous packages. Follow this guide to set up environment on your local machine.

Lecture Notes

The lecture notes are highly recommended optional readings for this course. It covers more advanced topics and provides additional context for concepts and algorithms covered in the lectures.

Paper Review

Taking this class for 4 units entails additionally completing a paper review by the end of the quarter. See the paper review requirements here.

Schedule

Subject to change. We will try to have the lecture slides and notes uploaded before each class period.