AI RESEARCH
RoboMD: Uncovering Robot Vulnerabilities through Semantic Potential Fields
arXiv CS.LG
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ArXi:2412.02818v3 Announce Type: replace-cross 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 vulnerabilities is hindered by two key challenges: (i) the relevant variations to test against are often unknown, and (ii) direct testing in the real world is costly and unsafe. We