activity
20242026
collaborators

7 papers

cs.RO2026

Do Vision-Language-Action Models Mean What They Say? On the Role of Faithfulness in Embodied Reasoning

Matthew Foutter, Matteo Cercola, Lena Wild +4

Embodied Chain-of-Thought has emerged as a promising mechanism to enhance robot decision-making and interpretability in black-box Vision-Language Action (VLA) models. However, whet…

cs.CV2025

Martian World Model: Controllable Video Synthesis with Physically Accurate 3D Reconstructions

Longfei Li, Zhiwen Fan, Wenyan Cong +10

Synthesizing realistic Martian landscape videos is crucial for mission rehearsal and robotic simulation. However, this task poses unique challenges due to the scarcity of high-qual…

cs.RO2025

RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models

Jacky Kwok, Christopher Agia, Rohan Sinha +5

Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in visuomotor control, yet ensuring their robustness in unstructured real-world environments remains a…

cs.CV2025

Vision Foundation Model Embedding-Based Semantic Anomaly Detection

Max Peter Ronecker, Matthew Foutter, Amine Elhafsi +4

Semantic anomalies are contextually invalid or unusual combinations of familiar visual elements that can cause undefined behavior and failures in system-level reasoning for autonom…

cs.RO2025

Space-LLaVA: a Vision-Language Model Adapted to Extraterrestrial Applications

Matthew Foutter, Daniele Gammelli, Justin Kruger +5

Foundation Models (FMs), e.g., large language models, possess attributes of intelligence which offer promise to endow a robot with the contextual understanding necessary to navigat…

math.OC2024

Realistic Extreme Behavior Generation for Improved AV Testing

Robert Dyro, Matthew Foutter, Ruolin Li +4

This work introduces a framework to diagnose the strengths and shortcomings of Autonomous Vehicle (AV) collision avoidance technology with synthetic yet realistic potential collisi…