2 citations · 5 across the 29 of their papers we have counts for
17 papers · 1 filter
Stochastic Nonlinear Model Predictive Control with Gaussian Mixture Uncertainty Propagation
Konstantinos Prattis, Luca Laurenti, Azita Dabiri
We propose a novel Stochastic Nonlinear Model Predictive Control (SNMPC) framework for nonlinear systems with additive noise. Building on recent advances in nonlinear uncertainty p…
Hybrid Energy-Based Models for Physical AI: Provably Stable Identification of Port-Hamiltonian Dynamics
Simone Betteti, Luca Laurenti
Energy-based models (EBMs) implement inference as gradient descent on a learned Lyapunov function, yielding interpretable, structure-preserving alternatives to black-box neural ODE…
StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
Rayan Mazouz, Frederik Baymler Mathiesen, Luca Laurenti +1
We present StochasticBarrier.jl, an open-source Julia-based toolbox for generating Stochastic Barrier Functions (SBFs) for safety verification of discrete-time stochastic systems w…
Piecewise Control Barrier Functions for Stochastic Systems
Rayan Mazouz, Luca Laurenti, Morteza Lahijanian
This paper presents a method for the simultaneous synthesis of a barrier certificate and a safe controller for discrete-time nonlinear stochastic systems. Our approach, based on pi…
Efficient Uncertainty Propagation with Guarantees in Wasserstein Distance
Eduardo Figueiredo, Steven Adams, Peyman Mohajerin Esfahani +1
In this paper, we consider the problem of propagating an uncertain distribution by a possibly non-linear function and quantifying the resulting uncertainty. We measure the uncertai…
Formal Uncertainty Propagation for Stochastic Dynamical Systems with Additive Noise
Steven Adams, Eduardo Figueiredo, Luca Laurenti
In this paper, we consider discrete-time non-linear stochastic dynamical systems with additive process noise in which both the initial state and noise distributions are uncertain.…
Memory-dependent abstractions of stochastic systems through the lens of transfer operators
Adrien Banse, Giannis Delimpaltadakis, Luca Laurenti +2
With the increasing ubiquity of safety-critical autonomous systems operating in uncertain environments, there is a need for mathematical methods for formal verification of stochast…
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…
Scalable control synthesis for stochastic systems via structural IMDP abstractions
Frederik Baymler Mathiesen, Sofie Haesaert, Luca Laurenti
This paper introduces a novel abstraction-based framework for controller synthesis of nonlinear discrete-time stochastic systems. The focus is on probabilistic reach-avoid specific…
A data-driven approach for safety quantification of non-linear stochastic systems with unknown additive noise distribution
Frederik Baymler Mathiesen, Licio Romao, Simeon C. Calvert +2
In this paper, we present a novel data-driven approach to quantify safety for non-linear, discrete-time stochastic systems with unknown noise distribution. We define safety as the…
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…
Uncertainty Propagation in Stochastic Systems via Mixture Models with Error Quantification
Eduardo Figueiredo, Andrea Patane, Morteza Lahijanian +1
Uncertainty propagation in non-linear dynamical systems has become a key problem in various fields including control theory and machine learning. In this work we focus on discrete-…
IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes
Frederik Baymler Mathiesen, Morteza Lahijanian, Luca Laurenti
In this paper, we present IntervalMDP.jl, a Julia package for probabilistic analysis of interval Markov Decision Processes (IMDPs). IntervalMDP.jl facilitates the synthesis of opti…
A Unifying Perspective for Safety of Stochastic Systems: From Barrier Functions to Finite Abstractions
Luca Laurenti, Morteza Lahijanian
Providing safety guarantees for stochastic dynamical systems is a central problem in various fields, including control theory, machine learning, and robotics. Existing methods eith…
Formal Abstraction of General Stochastic Systems via Noise Partitioning
John Skovbekk, Luca Laurenti, Eric Frew +1
Verifying the performance of safety-critical, stochastic systems with complex noise distributions is difficult. We introduce a general procedure for the finite abstraction of nonli…
Promises of Deep Kernel Learning for Control Synthesis
Robert Reed, Luca Laurenti, Morteza Lahijanian
Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising to…
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…