4 papers · 1 filter
RoboMD: Uncovering Robot Vulnerabilities through Semantic Potential Fields
Som Sagar, Jiafei Duan, Sreevishakh Vasudevan +4
Robot manipulation policies, while central to the promise of physical AI, are highly vulnerable in the presence of external variations in the real world. Diagnosing these vulnerabi…
BaTCAVe: Trustworthy Explanations for Robot Behaviors
Som Sagar, Aditya Taparia, Harsh Mankodiya +3
Black box neural networks are an indispensable part of modern robots. Nevertheless, deploying such high-stakes systems in real-world scenarios poses significant challenges when the…
Viewpoint-Agnostic Manipulation Policies with Strategic Vantage Selection
Sreevishakh Vasudevan, Som Sagar, Ransalu Senanayake
Since vision-based manipulation policies are typically trained from data gathered from a single viewpoint, their performance drops when the view changes during deployment. Naively…
PAC Bench: Do Foundation Models Understand Prerequisites for Executing Manipulation Policies?
Atharva Gundawar, Som Sagar, Ransalu Senanayake
Vision-Language Models (VLMs) are increasingly pivotal for generalist robot manipulation, enabling tasks such as physical reasoning, policy generation, and failure detection. Howev…