Course Description

Introduces the basic principles of robotics, focusing on core topics in autonomy and artificial intelligence, as well as their applications in self-driving cars, drones, and other types of robots. Students will learn the fundamentals of the autonomy software stack and related AI algorithms that allow robots to perform complex tasks like navigating an environment and detecting pedestrians.


  • Student Instructor: Rohan Raval
    • 4th year, BS Computer Science and Physics
  • Faculty Advisor: Nicola Bezzo
    • Assistant Professor, ECE and Systems Engineering

Course Structure

  • Attendance (50%)
    • Lectures will be once a week, 50 mins each. I will try my best to make lectures discussion-based as much as possible to foster engagement. There may also be guest lectures.
  • Readings (50%)
    • There will be a list of readings, from which students should pick one each week to write a short analysis. These readings will expand on concepts talked about in class and connect them with work being done in industry or academia.
    • Alternatively, for students that would like a more hands-on challenge, I will try to make optional programming assignments which can be completed instead of the readings. They will usually involve developing algorithms we talked about in class that week, and I will try to provide skeleton Python code whenever possible.
  • This course is a 1-credit P/F class.
  • As with any course, you will get out of it what you put into it! The idea behind this course is to present a sampling of concepts from which you can explore more about robotics – and in doing so, hopefully instill an interest in robotics (possibly as a profession!)
  • Course Github: link