{
  "id": 7608,
  "url": "https://arxiv.org/abs/2603.06130v1",
  "title": "A Hazard-Informed Data Pipeline for Robotics Physical Safety",
  "summary": "This report presents a structured Robotics Physical Safety Framework based on explicit asset declaration, systematic vulnerability enumeration, and hazard-driven synthetic data generation. The approach bridges classical risk engineering with modern machine learning pipelines, enabling safety envelope learning grounded in a formalized hazard ontology. The key contribution of this framework is the alignment between classical safety engineering, digital twin simulation, synthetic data generation, a",
  "authors": "Alexei Odinokov, Rostislav Yavorskiy",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-06T10:38:30.000Z",
  "fetched_at": "2026-07-14T16:33:21.049Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7608",
  "original_url": "https://arxiv.org/abs/2603.06130v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}