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arXiv AI By Vincenzo Guarino, Emanuele Musumeci, Vincenzo Suriani, Daniele Nardi

iAm.md: Robot Skill Self-Assessment through Agentic Introspection for Unknown Open-Vocabulary Domains

Read the original on arXiv AI →

The paper introduces iAm.md, a Markdown-based framework that enables robot skill self-assessment through agentic introspection. By mapping open‑vocabulary semantic detections and object segmentations to persistent records, the system anchors autonomous behavior generation in deployment evidence, mitigating grounding failures. Experiments on a simulated TIAGo robot demonstrate that this representation supports both skill self‑assessment and executable task generalization for navigation‑and‑manipulation tasks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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