From the 2 of 25 linked papers with an AI index.
25 papers
SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing
Zhouheng Li, Fangguo Zhao, Mattia Piccinini +6
Autonomous multi-vehicle racing requires real-time planning of diverse competitive behaviors in intense interactions. Existing planners often struggle to balance strategic diversit…
Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving
Yuan Gao, Wenting Miao, Mattia Piccinini +3
Chat2Scenic is an interactive, retrieval‑augmented framework that uses large language models to generate executable scenario scripts in a domain‑specific language for testing auton…
A Hybrid Sampling-Based Trajectory Planner with Game-Theoretic Guidance for Autonomous Racing
Alexander Langmann, Frederico Pita de Araujo, Mattia Piccinini +1
The paper introduces a hybrid planner that combines game-theoretic reasoning with a sampling-based motion planner to enable fast, strategic trajectory planning for autonomous racin…
Validate the Dream Before You Trust Its Verdict: Admissibility for World-Model Simulators
Christian Oefinger, Finn Rasmus Schäfer, Korbinian Moller +2
Across robotics, World Models (WMs) are increasingly used to evaluate action policies by simulating the consequences of actions in an imagined world, and returning a success or saf…
EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving
Finn Rasmus Schäfer, Yuan Gao, Dingrui Wang +5
While Vision-Language Models (VLMs) have advanced high-level reasoning in autonomous driving, their ability to ground this reasoning in the underlying physics of ego-motion remains…
Unified Video-Action Joint Denoising for Dexterous Action and Data Generation
Dingrui Wang, YuAn Wang, Jinkun Liu +4
Recent world action models leverage video foundation models by aligning broad visual-dynamics priors with executable robot actions. We revisit this alignment from a distributional…