12 citations · 12 across the 4 of their papers we have counts for
4 papers
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…
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam +4
Neural Networks (NNs) trained through supervised learning struggle with managing edge-case scenarios common in real-world driving due to the intractability of exhaustive datasets c…
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…
Mini Honor of Kings: A Lightweight Environment for Multi-Agent Reinforcement Learning
Lin Liu, Jian Zhao, Cheng Hu +9
Games are widely used as research environments for multi-agent reinforcement learning (MARL), but they pose three significant challenges: limited customization, high computational…