Research paper
Learning of Robot Safety Policies via Adversarial Synthetic Scenarios
The proposed architecture uses a red team to generate hazardous scenarios and a blue team to refine robot safety policies. The source explicitly describes ongoing work and a problem formulation. It is a testing/research concept, with demonstrated coverage and physical effectiveness still unreported in the abstract.
Reviewed 2026-11-05 · Source and bibliography checked
- Original title
- Learning of Robot Safety Policies via Adversarial Synthetic Scenarios
- Publisher
- arXiv
- Authors
- Dorofeev, Nikolai, Odinokov, Alexey, Yavorskiy, Rostislav
- DOI
- 10.48550/arxiv.2606.05952
- First archive posting
- 2026-06-04
- Source language
- en
- Source country
- US
- Edition
- v1
- Access
- Open archive metadata and manuscript
- Publication status
- Preprint
Related resources and engineering notes
Source overview
The proposed architecture uses a red team to generate hazardous scenarios and a blue team to refine robot safety policies. The source explicitly describes ongoing work and a problem formulation. It is a testing/research concept, with demonstrated coverage and physical effectiveness still unreported in the abstract.
Use and review
Original summary of the primary archive abstract and bibliographic record. Specialist technical and native-language review remain pending. The reported method does not establish a deployed safety function or achieved PL.
Sources & editions
Learning of Robot Safety Policies via Adversarial Synthetic Scenarios ↗
arXiv · v1
arXiv abstract, authors, submission history and DOI links; first posting 2026-06-04, abstract reviewed in v1. Publisher dates are separate.