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TII-EuroRacing Team in Pole Position at Autonomous Challenge @CES 2022 in Las Vegas

TII · · Robotics Partnership

Technology Innovation Institute (TII) and the University of Modena and Reggio Emilia are participating as Team TII-EuroRacing in the Autonomous Challenge at CES 2022 in Las Vegas. TII is also a premier sponsor of the event, which features head-to-head autonomous racecar competition at the Las Vegas Motor Speedway. Team TII-EuroRacing will compete with its DO12 racecar, a Dallara AV-21 retrofitted for automation, after making it to the finals at the Indy Autonomous Challenge in October 2021. Why it matters: This event highlights the UAE's commitment to advancing autonomous robotics and positions TII as a leader in the development of autonomous racing systems.

Minimalistic Autonomous Stack for High-Speed Time-Trial Racing

arXiv · · Robotics RL

This paper introduces a minimalistic autonomous racing stack designed for high-speed time-trial racing, emphasizing rapid deployment and efficient system integration with minimal on-track testing. Validated on real speedways, the stack achieved a top speed of 206 km/h within just 11 hours of practice, covering 325 km. The system performance analysis includes tracking accuracy, vehicle dynamics, and safety considerations. Why it matters: This research offers insights for teams aiming to quickly develop and deploy autonomous racing stacks with limited track access, potentially accelerating innovation in autonomous vehicle technology within the A2RL and similar racing initiatives.

Bayesian Optimization-based Tire Parameter and Uncertainty Estimation for Real-World Data

arXiv · · RL Robotics

This paper introduces a Bayesian optimization method for estimating tire parameters and their uncertainty, addressing a gap in existing literature. The methodology uses Stochastic Variational Inference to estimate parameters and uncertainties, and it is validated against a Nelder-Mead algorithm. The approach is applied to real-world data from the Abu Dhabi Autonomous Racing League, revealing uncertainties in identifying curvature and shape parameters due to insufficient excitation. Why it matters: The research provides a practical tool for assessing tire model parameters in real-world conditions, with implications for autonomous racing and vehicle dynamics modeling in the GCC region.

Discover the Future of Autonomous Vehicles in upcoming MBZUAI Talks webinar

MBZUAI · · AI Autonomous Vehicles

MBZUAI will host a webinar on November 3 featuring Professor Daniela Rus from MIT CSAIL, focusing on the role of AI in autonomous vehicles. The webinar will explore integrating risk assessment, behavior analysis, and intelligent situation awareness into autonomous mobility. Dr. Behjat Al Yousuf will moderate the session, which is part of the MBZUAI Talks series. Why it matters: This event highlights MBZUAI's role as a hub for AI discourse and its focus on advancing research and development in autonomous transportation within the region.