Here is what current F1Tenth users say:

I learned the subject entirely from F1Tenth and I created a new course in my department following the f1tenth course materials. The course became the most popular course in the department over the last 4 years.

I took F1Tenth Autonomous Robots course at UT Austin and I would highly recommend taking this course for anyone who wants to foray into the field of autonomous vehicles. This course was successful in covering all the basics for estimation, mapping, and obstacle avoidance. Deploying these algorithms on actual cars is also fun with a great learning curve and is something every roboticist should experience.

I took the F1Tenth autonomous racing course during my masters at UPenn and it was no doubt one of the best courses there. It was a very hands-on course and I got to implement various motion planning, perception, and control algorithms on the F1/10 car. Understanding the theory, coding up the algorithms, and debugging issues that arose during hardware implementation taught me invaluable lessons and made me ready for the challenges that I would face in real-world scenarios. This experience solidified my decision to delve deeper into the field and pursue a Ph.D. in Autonomous Systems at Washington University at St. Louis.

F1Tenth was by far the most fun class I’ve taken at Penn! It was very rewarding, and the combination of labs and racing made the course super exciting. I learned a lot about general control algorithms, as well as specific and practical aspects of self driving vehicles. The freedom granted in the final project really let everyone explore their own unique ideas, and it was inspiring seeing my classmates try all sorts of applications. 10/10 would recommend!

My experience as a core member of CMU’s F1Tenth team provided unparalleled growth in my skills across perception, planning, and control in autonomous systems. Through building and optimizing a 1:10 scale autonomous race car, incorporating techniques like SLAM, state estimation, raceline optimization, and various control algorithms, I gained hands-on expertise in seamlessly integrating planning and control from simulation to hardware.

I’ve began using F1Tenth as an affordable way to introduce myself to path planning, graph search, and control algorithms for my graduate research. I would recommend F1Tenth to anyone looking for a feasible, fun way to apply research knowledge to a tangible and capable platform!

I came into F1Tenth with zero robotics experience, only an embedded programming background. The F1Tenth course was able to get me up to speed quickly on basic robotics concepts, in particular, planning and control algorithms beyond basic A*Star and PID. The competitions have provided a great opportunity to work with a team and apply the knowledge from the course.

Developing a race stack for an autonomous mobile robot involves designing and implementing a full see-think-act cycle. When developing this for a racecar, one has to uniquely put extra effort to get things right.

I'm new in the field, but F1Tenth doc helped me start building F1Tenth vehicle, and all material is very helpfull to connect the dots. Compiled BOM list is also very helpfull to gather all the components.

The F1Tenth gave us the perfect platform to learn and strengthen our skills in mobile robotics. The competition is thrilling and serves as a great motivation for everyone to push their comprehension even further.

Thanks to F1Tenth I had the ability to apply the theoretical skills I learned in my studies to a real robotics system. I introduced me to cooperating with a team on a large software stack. Also looking at the great work the F1Tenth community is doing all over the world inspired me for my own work.

F1Tenth has been an invaluable platform for our research group to demonstrate our simulated experiments in the physical world. We have used the F1Tenth autonomous driving platform to demonstrate our differentiable physics simulation experiments in the real world as well as our system identification, adaptive control and applied reinforcement learning algorithms.

F1Tenth has given me a great opportunity to learn skills in a very hands-on manner, be it with a simulator or actually running the algorithms on the car. It is also extremely fun and challenging to implement techniques that take the least amount of time to execute.

F1Tenth has been an invaluable platform for enhancing my skills in perception, planning, and control within the realm of autonomous vehicles. Through its hands-on approach and real-world challenges, I've gained practical experience in sensor fusion, path planning, and decision-making algorithms, allowing me to apply cutting-edge techniques to real-world scenarios with confidence and precision.

I have been involved with robotics since middle school, however F1Tenth has helped me learn robotics tools that I would need for real world applications. I have learned how to use ROS and ROS2 through Linux. With the presentation slides and lecture videos, I have learned to develop controls and planning algorithms.

F1Tenth introduced me to robotics. Without it, I would not be the roboticist I am today. It is the perfect platform for hands-on learning.

Especially thanks to the hands-on experience. Learning about all the mentioned parts (perception/planning/control) is complex, but having the real experience is really game-changing. I can observe this effect on students getting in touch of F1Tenth as well.

The F1Tenth project stands as an invaluable resource for anyone passionate about engineering, integrating the latest technologies and innovative ideas across various domains, including electrical/electronics, mechanical engineering, and computer science. Its hands-on approach and focus on real-world applications arm students with advanced techniques and comprehensive understanding of autonomous systems.

As an undergrad student, F1Tenth was a way for me to enter in the research world and learn things that I would never have learned in my classes. It allows us to push further and go faster on the tracks!

Davis F1Tenth has been a great opportunity to partake multidisciplinary engineering work! We have been working closely with mechanical, electrical, and computer engineers to get our car race ready. Having a vibrant and support community around this project has been a great addition!

F1Tenth was an engaging introduction to topics in robotics such as localization, path planning, and kinematic models. Going from boxes of parts to a functioning car has helped me mature as an engineer and inspired me to major in Computer Engineering.

F1Tenth has been a wonderful way to learn first-hand about advanced techniques in robotics. Being able to see the algorithms work in real life has been a wonderful motivating example to study more abstract concepts. The competition aspect keeps it continually interesting as well.

I am a team member at the University of Toronto (Mississauga Campus) Robotics club. Last month we came across F1Tenth and it immediately caught out eye. We think this would be a great project for our club, as it can greatly engage our club member's. We are currently planning our budget to see which parts we can buy this semester and which one's we can buy next semester.

The software and hardware architecture of the platform has helped us power up our path planning, control, and robot motion classes. We have trained several generations of successful and highly trained engineers. The platform can be easily updated and upgraded to the current needs of the state state of the art.

Thanks to the F1Tenth competition, I improved my skills in GPU acceleration. Indeed, I accelerated algorithms for perception and planning on GPU to meet deadlines imposed by the racing scenario.

F1Tenth is the total a full gift set for learning autonomous mobile. With F1Tenth, I have learned SLAM, path planning, pure pursuit and other special driving algorithms. F1Tenth helps me adventure the Uncharted territory.