12 citations · 19 across the 4 of their papers we have counts for
5 papers · 1 filter
Drive Fast, Learn Faster: On-Board RL for High Performance Autonomous Racing
Benedict Hildisch, Edoardo Ghignone, Nicolas Baumann +3
Autonomous racing presents unique challenges due to its non-linear dynamics, the high speed involved, and the critical need for real-time decision-making under dynamic and unpredic…
RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms
Edoardo Ghignone, Nicolas Baumann, Cheng Hu +4
Autonomous racing presents a complex environment requiring robust controllers capable of making rapid decisions under dynamic conditions. While traditional controllers based on tir…
Predictive Spliner: Data-Driven Overtaking in Autonomous Racing Using Opponent Trajectory Prediction
Nicolas Baumann, Edoardo Ghignone, Cheng Hu +6
Head-to-head racing against opponents is a challenging and emerging topic in the domain of autonomous racing. We propose Predictive Spliner, a data-driven overtaking planner that l…
Learning-Based On-Track System Identification for Scaled Autonomous Racing in Under a Minute
Onur Dikici, Edoardo Ghignone, Cheng Hu +5
Accurate tire modeling is crucial for optimizing autonomous racing vehicles, as state-of-the-art (SotA) model-based techniques rely on precise knowledge of the vehicle's parameters…
ForzaETH Race Stack -- Scaled Autonomous Head-to-Head Racing on Fully Commercial off-the-Shelf Hardware
Nicolas Baumann, Edoardo Ghignone, Jonas Kühne +11
Autonomous racing in robotics combines high-speed dynamics with the necessity for reliability and real-time decision-making. While such racing pushes software and hardware to their…