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This paper presents a data-efficient framework for real-time monitoring of robotic systems operating under uncertainty, specifically addressing safety specifications in maritime navigation without relying on explicit probability distributions. By leveraging reachable sets derived from limited data, the approach demonstrates improved risk detection capabilities compared to current state-of-the-art metrics through both simulation and hardware experiments. The work advances the field by enabling robust specification evaluation for autonomous agents where traditional statistical models are impractical or unavailable.
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Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

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arXiv:2608.02811v1 Announce Type: new Abstract: Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty remains challenging, as existing formulations typically require extensive data or explicit uncertainty distributions. In this paper, we propose a real-time monitoring framework that reduces data requirements by leveraging data-driven reachable sets for specification evaluation. We instantiate the framework for maritime navigation, where complex specifications arise from traffic rules. We develop a data-efficient pipeline for constructing reachable sets and derive a monitoring formulation suitable for real-time deployment. Simulation and hardware experiments demonstrate robust monitoring under realistic disturbances, achieving improved risk detection compared to state-of-the-art metrics.

Abstract:Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty remains challenging, as existing formulations typically require extensive data or explicit uncertainty distributions. In this paper, we propose a real-time monitoring framework that reduces data requirements by leveraging data-driven reachable sets for specification evaluation. We instantiate the framework for maritime navigation, where complex specifications arise from traffic rules. We develop a data-efficient pipeline for constructing reachable sets and derive a monitoring formulation suitable for real-time deployment. Simulation and hardware experiments demonstrate robust monitoring under realistic disturbances, achieving improved risk detection compared to state-of-the-art metrics.

Robotics (cs.RO); Systems and Control (eess.SY)

arXiv:2608.02811 [cs.RO]

(or arXiv:2608.02811v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2608.02811 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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