In recent years there has been a rapid development in agile robots capable of operating at their limits in dynamic environments. Autonomous racing and recent developments in it also spurred by competitions such as the Indy Autonomous Challenge, A2RL, and F1Tenth have shown how modern autonomous control algorithms are capable of operating racecars at their handling limits and also possibly capable of beating humans in the near future. What becomes challenging for such agile robots is their need to adapt rapidly to changing environmental conditions like surface change due to tire degradation, weather change, tire temperature changes in racing; and also the need to maintain a high control frequency necessary to execute such demanding tasks. The robots also need to stay safe while executing such tasks.
Related Publications:
- Adaptive Planning and Control with Time-Varying Tire Models for Autonomous Racing Using Extreme Learning Machine, Dvij Kalaria*, Qin Lin, and John M. Dolan, IEEE International Conference on Robotics and Automation (ICRA), 2024 [Paper][Video][Project Website]
- Towards Safety Assured End-to-End Vision-Based Control for Autonomous Racing, Dvij Kalaria*, Qin Lin, and John M. Dolan, IFAC World Congress, 2023 [Paper][Video]
- Delay-aware Robust Control for Safe Autonomous Driving and Racing, Dvij Kalaria*, Qin Lin, and John M. Dolan, IEEE Transactions on Intelligent Transportation Systems, 2023 [Paper][Video]