RAGE: A Tightly Coupled Radar-Aided Grip Estimator For Autonomous Race Cars
Davide Malvezzi, Nicola Musiu, Eugenio Mascaro, Francesco Iacovacci, Marko Bertogna
TLDR
RAGE is a novel real-time estimator for autonomous race cars that infers vehicle dynamics and tire grip using only standard IMU and RADAR sensors.
Key contributions
- Estimates vehicle velocity, tire slip angles, and lateral forces simultaneously.
- Utilizes only standard IMU and RADAR sensors, avoiding costly specialized hardware.
- Validated through high-fidelity simulations and real-world experiments on an autonomous race car.
- Enables safe and effective operation of autonomous race cars at their physical limits.
Why it matters
Traditional tire grip estimation often requires expensive, custom sensors, limiting scalability. RAGE provides a cost-effective solution by using commonly available sensors. This innovation allows autonomous race cars to operate more safely and effectively at their performance limits, enhancing deployment.
Original Abstract
Real-time estimation of vehicle-tire-road friction is critical for allowing autonomous race cars to safely and effectively operate at their physical limits. Traditional approaches to measure tire grip often depend on costly, specialized sensors that require custom installation, limiting scalability and deployment. In this work, we introduce RAGE, a novel real-time estimator that simultaneously infers the vehicle velocity, slip angles of the tires and the lateral forces that act on them, using only standard sensors, such as IMUs and RADARs, which are commonly available on most of modern autonomous platforms. We validate our approach through both high-fidelity simulations and real-world experiments conducted on the EAV-24 autonomous race car, demonstrating the accuracy and effectiveness of our method in estimating the vehicle lateral dynamics.
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