arXiv
Open Access
2026
A Hazard-Informed Data Pipeline for Robotics Physical Safety
Alexei Odinokov
Rostislav Yavorskiy
Abstrak
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, and machine learning model training.
Penulis (2)
A
Alexei Odinokov
R
Rostislav Yavorskiy
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2026
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- en
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- arXiv
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- Open Access ✓