Situation Awareness in AI-Generated Industrial Cyber-Physical Systems

Abstract:

Abstract Modern industrial environments increasingly rely on close cooperation between humans and autonomous devices, such as collaborative robots, a relationship that requires reliable situation awareness. At the same time, the AI coding agents (with underlying LLMs) enable a new development paradigm, allowing controllers to be generated from high-level descriptions rather than being implemented manually. While this approach accelerates development, it raises concerns about correctness and safety. In this paper, we propose a method that complements AI-generated controllers with explicit situational descriptions of safety constraints. Instead of addressing safety throughout the control logic, we do so through declarative descriptions of relevant situations and the constraints that must hold in these situations. This enables a clear separation between functional behavior and safety requirements, allowing safety concerns to be expressed independently and concisely. We demonstrate the proposed method on a real-life collaborative human–robot scenario from an ongoing international project.

BibTeX:

@inproceedings{bures_situation_2027,
    title = {{Situation Awareness in AI-Generated Industrial Cyber-Physical Systems}},
    author = {Bureš, Tomáš and Hnětynka, Petr and Plášil, František},
    year = {2027},
    booktitle = {{Proceedings of ISOLA 2026, Kos, Greece}},
    publisher = {Springer},
    series = {{LNCS}},
    number = {17141},
    doi = {10.1007/978-3-032-40108-3_7},
    pages = {107--125},
}

Proceedings paper