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20242026
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cs.RO2026

DOT-Sim: Differentiable Optical Tactile Simulation with Precise Real-to-Sim Physical Calibration

Yang You, Won Kyung Do, Aiden Swann +3

Simulating optical tactile sensors presents significant challenges due to their high deformability and intricate optical properties. To address these issues and enable a physically…

cs.RO2026

, But Make It Fly: Physics-Guided Transfer of VLA Models to Aerial Manipulation

Johnathan Tucker, Denis Liu, Aiden Swann +7

Vision-Language-Action (VLA) models such as have demonstrated remarkable generalization across diverse fixed-base manipulators. However, transferring these foundation models…

cs.RO2026

Observing and Controlling Features in Vision-Language-Action Models

Hugo Buurmeijer, Carmen Amo Alonso, Aiden Swann +1

Vision-Language-Action Models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that of Large Language Models (LLMs)…

cs.RO2026

Sparse Autoencoders Reveal Interpretable and Steerable Features in VLA Models

Aiden Swann, Lachlain McGranahan, Hugo Buurmeijer +2

Vision-Language-Action (VLA) models have emerged as a promising approach for general-purpose robot manipulation. However, little research has mechanistically explored when and why…

cs.RO2025

Semantic-Metric Bayesian Risk Fields: Learning Robot Safety from Human Videos with a VLM Prior

Timothy Chen, Marcus Dominguez-Kuhne, Aiden Swann +2

Humans interpret safety not as a binary signal but as a continuous, context- and spatially-dependent notion of risk. While risk is subjective, humans form rational mental models th…

cs.RO2025

Phys2Real: Fusing VLM Priors with Interactive Online Adaptation for Uncertainty-Aware Sim-to-Real Manipulation

Maggie Wang, Stephen Tian, Aiden Swann +3

Learning robotic manipulation policies directly in the real world can be expensive and time-consuming. While reinforcement learning (RL) policies trained in simulation present a sc…