activity
20222026
collaborators

8 papers

cs.RO2026

Provably Safe Motion Planning Under Unknown Disturbances

Ibon Gracia, Qi Heng Ho, Luca Laurenti +1

We present a provably safe sampling-based motion planning algorithm for robotic systems affected by random disturbances of unknown distribution. We consider systems with linear or…

eess.SY2026

On the Optimality of Uncertain MDP Abstractions

Ibon Gracia, Morteza Lahijanian

We study the asymptotic optimality of abstraction-based control synthesis algorithms. Specifically, we consider uncertain MDP (UMDP) abstraction, and investigate whether refinement…

eess.SY2026

Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs

Chun-Wei Kong, Sebastian Escobar, Ibon Gracia +2

Due to their expressive power, neural networks (NNs) are promising templates for functional optimization problems, particularly for reach-avoid certificate generation for systems g…

eess.SY2025

Data-Driven Control via Conditional Mean Embeddings: Formal Guarantees via Uncertain MDP Abstraction

Ibon Gracia, Morteza Lahijanian

Controlling stochastic systems with unknown dynamics and under complex specifications is specially challenging in safety-critical settings, where performance guarantees are essenti…

eess.SY2025

Beyond Interval MDPs: Tight and Efficient Abstractions of Stochastic Systems

Ibon Gracia, Morteza Lahijanian

This work addresses the general problem of control synthesis for continuous-space, discrete-time stochastic systems with probabilistic guarantees via finite abstractions. While est…

eess.SY2024

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances

Ibon Gracia, Luca Laurenti, Manuel Mazo +2

In this paper, we present a novel framework to synthesize robust strategies for discrete-time nonlinear systems with random disturbances that are unknown, against temporal logic sp…

eess.SY2024

Data-Driven Strategy Synthesis for Stochastic Systems with Unknown Nonlinear Disturbances

Ibon Gracia, Dimitris Boskos, Luca Laurenti +1

In this paper, we introduce a data-driven framework for synthesis of provably-correct controllers for general nonlinear switched systems under complex specifications. The focus is…

eess.SY2022

Efficient Strategy Synthesis for Switched Stochastic Systems with Distributional Uncertainty

Ibon Gracia, Dimitris Boskos, Morteza Lahijanian +2

We introduce a framework for the control of discrete-time switched stochastic systems with uncertain distributions. In particular, we consider stochastic dynamics with additive noi…