Intelligent Robotic Systems

New course developed at Princeton University - ECE346

ECE 346: Intelligent Robotic Systems is an undergraduate robotics course at Princeton University that combines foundational autonomy theory with hands-on practice on real robot trucks. Students learn core concepts in perception, planning, control, and safety while building and programming mobile robotic systems using the Robot Operating System (ROS).

The accompanying ECE346 codebase on GitHub provides a complete set of lab materials, development tools, simulation scaffolding, and robot interface code. It supports a sequence of labs that guide students from basic ROS fundamentals to advanced autonomy topics such as trajectory planning, collision avoidance, and imitation learning.

Robotic Platform — 1/16-Scale Autonomous Truck

The hardware platform for ECE 346 consists of 1/16-scale ground robot trucks outfitted with onboard computation, sensors, and ROS connectivity. These mini autonomous vehicles serve as a physical testbed for core autonomy algorithms and allow students to iterate between simulation and real robot testing.

In the first-year offering of the course, we built 16 of these trucks:

Figure: The 1/16-scaled robotic trucks used for ECE 346.

Minicity

In addition to the truck, we also built a test room for the course: a minicity with intersections, merge lanes, roundabouts, etc. The room is also equipped with SLAM for real-time localization:

Figure: The Minicity test room for ECE 346.

Codebase — ECE346 GitHub Repository

The SafeRoboticsLab/ECE346 repository provides structured lab materials, ROS workspaces, and example packages used throughout the course.

Lab Assignments A progressive set of labs designed to teach robotics fundamentals through practice:

  • Lab 1: Introduction to ROS and basic truck operation
  • Lab 2: ILQR trajectory planning
  • Lab 3: Collision avoidance and dynamic environment navigation
  • Lab 4: MDP/POMDP decision making fundamentals
  • Lab 5: Imitation learning frameworks (More modules may be added in future iterations.)

Demo

The following figure shows the truck performing real-time iLQR to nagivate around the Minicity while following traffic rules and road boundaries:

Figure: A test run showing the truck performing real-time iLQR in Minicity.

Press release

The course is now one of the core courses for the Princeton’s Minor in Robotics.

The university also wrote a press release on the course, found here: Robot trucks drive students to solve real problems in modern robotics

Video: Official advertisement video from Princeton University featuring ECE 346.

Acknowledgement

Throughout the development of the hardware platform, software stack, and lab materials for this course, I significantly expanded my own technical skill set and understanding of full-stack robotic systems. Many of these lessons have directly carried over to larger-scale and more complex robotics projects that I have since had the opportunity to work on.

I am grateful to Professor Jaime Fernández Fisac for the opportunity to take on this challenge, and to my collaborators Zixu Zhang and Kai-Chieh Hsu.