Ontology-Driven Robotic Specification Synthesis

• URL: http://arxiv.org/abs/2602.05456v1
• Date: Thu, 05 Feb 2026 08:59:23 GMT
• Title: Ontology-Driven Robotic Specification Synthesis
• Authors: Maksym Figat, Ryan M. Mackey, Michel D. Ingham,
• Abstract summary: This paper addresses robotic system engineering for safety- and mission-critical applications by bridging the gap between high-level objectives and formal, executable specifications.<n>The proposed method is an hierarchical approach using timed Petri nets with resources, enabling Monte Carlo simulations at mission, system, and subsystem levels.
• Score: 0.38233569758620045
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper addresses robotic system engineering for safety- and mission-critical applications by bridging the gap between high-level objectives and formal, executable specifications. The proposed method, Robotic System Task to Model Transformation Methodology (RSTM2) is an ontology-driven, hierarchical approach using stochastic timed Petri nets with resources, enabling Monte Carlo simulations at mission, system, and subsystem levels. A hypothetical case study demonstrates how the RSTM2 method supports architectural trades, resource allocation, and performance analysis under uncertainty. Ontological concepts further enable explainable AI-based assistants, facilitating fully autonomous specification synthesis. The methodology offers particular benefits to complex multi-robot systems, such as the NASA CADRE mission, representing decentralized, resource-aware, and adaptive autonomous systems of the future.

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