Artificial Intelligence has enabled breakthroughs once thought impossible—from robotic systems detecting harvesting ripe fruit with remarkable efficiency to autonomous drones performing high-speed aerial acrobatics with split-second precision. Yet, the frontier of pushing both speed and accuracy in AI-powered robotics remains one of the most exciting challenges. This project aims to push those boundaries further by designing and developing a superfast autonomous racing vehicle capable of navigating a track at the highest possible speed—without going off-course. What You’ll Work On • Investigating innovative approaches to feedback control systems that integrate sensing, computation, and actuation. • Experimenting with event-based sensing modules for ultra-fast perception and decision-making. • Leveraging cutting-edge hardware accelerators for real-time, high-performance control. • Testing algorithms in racing scenarios where milliseconds matter. What You’ll Gain • Hands-on experience with state-of-the-art robotics hardware and AI methods. • The chance to contribute to a system where split-second control determines success or failure. • Mentorship and collaboration with researchers passionate about autonomy, robotics, and control theory. • An opportunity to work on a project that combines the thrill of racing with the rigor of advanced engineering. Applicants should have: • A strong background in robotics and control systems. • Practical experience with Linux, Python, and C++ programming. • Enthusiasm for tackling real-time, high-speed robotics challenges. • Creativity and curiosity to explore unconventional approaches to autonomy.

Participating students will be active contributors to the development of the autonomous racing car system. Specifically, they are expected to: • Contribute to hardware integration by assembling, configuring, and fine-tuning sensing, computation, and actuation modules. • Design and implement control and perception algorithms that enable high-speed, real-time decision-making on the race track. • Conduct systematic testing and validation, including simulation-based evaluations and on-track experiments, to ensure reliability and safety at extreme speeds. • Analyze performance data to refine both hardware and software components, identifying bottlenecks and proposing improvements. • Document progress and outcomes through written reports, presentations, and demonstrations, contributing to both technical dissemination and team knowledge-sharing. • Collaborate in a team-based research environment, participating in discussions, code reviews, and design iterations.