Session 2

F1TENTH Racing

Build and Compete with Autonomous Racing Cars

In this program, students explore robotics through 1/10-scale Formula-style race cars while learning how real self-driving cars are built and programmed. They assemble, code, test, and race their own robotic vehicles, using sensors, onboard computers, and software to help the cars see their surroundings and make decisions.

Curriculum

Students learn how a robotic race car moves by exploring its chassis, wheels, suspension, speed, balance, and steering. They then work with the sensors, circuits, and control systems that help a Formula 1/10 car navigate a real track. Through hands-on activities, students build programming skills and see how autonomous systems are designed to be fast, reliable, and safe. The program emphasizes teamwork, experimentation, and problem-solving. By the end of the program, students will be able to:

  • Learn beginner-friendly programming in Python or C/C++
  • Work with Arduino UNO and NVIDIA Jetson Orin Nano systems
  • Program the car to move, turn, stop, and follow lanes or walls
  • Understand the mechanical systems that make the car stable and responsive
  • Use sensors such as cameras, LiDAR, and IMUs to detect motion and surroundings
  • Explore how autonomous cars follow paths and avoid obstacles
  • Test and race their cars in both remote-controlled and autonomous modes
  • Gain a strong introduction to robotics and AI concepts

No prior robotics experience is required—just curiosity and a willingness to learn.

F1TENTH car and the computer
Planned Topics

The program is organized around the following core topics:

  • Introduction to the F1TENTH racing format, vehicle platform, sensors, and system design
  • Driving and control modes, including remote control and autonomous operation
  • Setting up the robot operating system and configuring the Jetson computer platform
  • Power systems, safety, and electrical circuits, including batteries and wheel control
  • Sensor integration, including LiDAR, depth cameras, and IMUs for navigation and positioning
  • Track navigation and racing on indoor and outdoor courses while avoiding obstacles safely
Request more information
Summer Institute Logo
Dongbin Lee
Faculty Lead
Don Lee

Assistant Professor, ECPE (SOECS)

Ph.D., Clemson University, 2009

Dr. Dongbin "Don" Lee is an assistant professor in the School of Engineering and Computer Science at Pacific. He has expertise and interest in uncrewed robotic systems and AI/deep/machine learning techniques in application to self-driving autonomous vehicles, smart farmers-centered sustainable precision agriculture tech along with humanoids, drones and submersible vehicles.

View Profile
Take the Next Step
Request More Information
Register Now