Instructor: Brian Hou (bhou at cs)

TA: Zoey Chen (qiuyuc at cs)
TA: Kay Ke (kayke at cs)
TA: Mohit Shridhar (mshr at cs)
TA: Nick Walker (nswalker at cs)

Lecture: MWF 1:30 - 2:30pm, Zoom (link on Canvas)
Office Hours: MWF 2:30 - 3:30pm (Brian), M 5:00-6:00pm (TAs), Th 1:30 - 3:30pm (TAs)


CSE 478 is a project- and discussion-based introduction to robotics. Autonomous vehicles will be used as a running example to introduce the algorithmic building blocks of robotics, and students may use the MuSHR rally car platform to gain hands-on experience. Students will reflect on the human and social impact of autonomy by reading and responding to essays, research papers, book chapters, and other relevant material.

By the end of this course, students should be able to:

  • Identify fundamental abstractions used by mobile robots in the wild (localization, planning, control), explain how they interact, and analyze algorithmic trade-offs within each abstraction.
  • Implement the above abstractions to enable a simulated mobile robot to navigate safely and efficiently, using Python and the Robot Operating System (ROS). Conduct principled robot experiments to diagnose and fix bugs across the mobile robot software stack.
  • Develop standards for ethical behavior in robotics and identify everyday ethical concerns in industrial and research contexts. Critique the human and social impact of autonomous systems.


This schedule is tentative and subject to change.

March 29 Intro to Robotics
March 31 Uber Accident Report (National Transportation Safety Board)
April 2 Do Artifacts Have Politics? (Langdon Winner)
April 5 Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction (Madeleine Clare Elish)
April 7 Intro to State Estimation
April 9 Probabilistic Motion and Sensor Models Project 1: Introduction
April 12 Particle Filtering
April 14 Kalman Filtering
April 16 No Lecture: MuSHR Lab Safety Training
April 19 Intro to Feedback Control
April 21 PID Control
April 23 Guest Lecture: Robotics and the Law (Ryan Calo)
April 26 Pure Pursuit and Model-Predictive Control Project 2: Localization
April 28 Linear Quadratic Regulator
April 30 Robot Rights? Let’s Talk about Human Welfare Instead (Abeba Birhane)
May 3 Intro to Planning
May 5 Heuristic Search
May 7 Guest Lecture: Jobs and Automation (Naveena Karusala)
May 10 Sampling-Based Motion Planning
May 12 Lazy Search and Planning for Vehicles
May 14 Robots in Society, Society in Robots (Selma Šabanović) Project 3: Control
May 17 Anatomy of an AI System (Kate Crawford, Vladan Joler)
May 19 Guest Lecture: Agricultural Robotics (Vivek Nayak)
May 21 Reinforcement Learning
May 24 Guest Lecture: Imitation Learning (Kay Ke)
May 26 Guest Lecture: Motion Planning at Waymo for Autonomously Driven Vehicles (Michael Koval)
May 28 Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI (Philip E. Agre)
May 31 Holiday: Memorial Day Project 4: Planning
June 2 Guest Lecture: Why Is Driving With Humans Hard? (Sanjiban Choudhury)
June 4 Conclusion


We thank past instructors Sanjiban Choudhury and Chris Mavrogiannis for sharing their course materials and insight, as well as the MuSHR team for their software and hardware assistance.