Cover Image

Provably Safe Motion Planning Under Unknown Disturbances

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gracia, Ibon, Ho, Qi Heng, Laurenti, Luca, Lahijanian, Morteza
Format:	Preprint
Published:	2026
Subjects:	Robotics Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data-Driven Strategy Synthesis for Stochastic Systems with Unknown Nonlinear Disturbances
by: Gracia, Ibon, et al.
Published: (2024)

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances
by: Gracia, Ibon, et al.
Published: (2024)

On the Optimality of Uncertain MDP Abstractions
by: Gracia, Ibon, et al.
Published: (2026)

Data-Driven Control via Conditional Mean Embeddings: Formal Guarantees via Uncertain MDP Abstraction
by: Gracia, Ibon, et al.
Published: (2025)

Beyond Interval MDPs: Tight and Efficient Abstractions of Stochastic Systems
by: Gracia, Ibon, et al.
Published: (2025)

Data-Driven Permissible Safe Control with Barrier Certificates
by: Mazouz, Rayan, et al.
Published: (2024)

Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
by: Mazouz, Rayan, et al.
Published: (2022)

Efficient Strategy Synthesis for Switched Stochastic Systems with Distributional Uncertainty
by: Gracia, Ibon, et al.
Published: (2022)

A Unifying Perspective for Safety of Stochastic Systems: From Barrier Functions to Finite Abstractions
by: Laurenti, Luca, et al.
Published: (2023)

RTD-RAX: Fast, Safe Trajectory Planning for Systems under Unknown Disturbances
by: Morales-Cuadrado, Evanns, et al.
Published: (2026)

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
by: Skovbekk, John, et al.
Published: (2021)

Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints
by: Cherenson, Daniel M., et al.
Published: (2025)

Piecewise Control Barrier Functions for Stochastic Systems
by: Mazouz, Rayan, et al.
Published: (2025)

Learning-Based Shielding for Safe Autonomy under Unknown Dynamics
by: Reed, Robert, et al.
Published: (2024)

Time-Varying Reach-Avoid Control Certificates for Stochastic Systems
by: Mazouz, Rayan, et al.
Published: (2026)

Promises of Deep Kernel Learning for Control Synthesis
by: Reed, Robert, et al.
Published: (2023)

Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives
by: Ho, Qi Heng, et al.
Published: (2024)

Uncertainty Propagation in Stochastic Systems via Mixture Models with Error Quantification
by: Figueiredo, Eduardo, et al.
Published: (2024)

Extended Version: Multi-Robot Motion Planning with Cooperative Localization
by: Theurkauf, Anne, et al.
Published: (2025)

Sampling-based Task and Kinodynamic Motion Planning under Semantic Uncertainty
by: Ho, Qi Heng, et al.
Published: (2026)

IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes
by: Mathiesen, Frederik Baymler, et al.
Published: (2024)

StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
by: Mazouz, Rayan, et al.
Published: (2026)

Falsification of Autonomous Systems in Rich Environments
by: Elimelech, Khen, et al.
Published: (2024)

Motion Planning and Control with Unknown Nonlinear Dynamics through Predicted Reachability
by: Zhang, Zhiquan, et al.
Published: (2025)

Distributionally Robust Safe Motion Planning with Contextual Information
by: Rahaman, Kaizer, et al.
Published: (2025)

Meta-Learning Augmented MPC for Disturbance-Aware Motion Planning and Control of Quadrotors
by: Lapandić, Dženan, et al.
Published: (2024)

A Modular Framework for Motion Planning using Safe-by-Design Motion Primitives
by: Vukosavljev, Marijan, et al.
Published: (2019)

SafeFlow: Safe Robot Motion Planning with Flow Matching via Control Barrier Functions
by: Dai, Xiaobing, et al.
Published: (2025)

An Efficient Reachability-Based Framework for Provably Safe Autonomous Navigation in Unknown Environments
by: Bajcsy, Andrea, et al.
Published: (2019)

Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
by: Kong, Chun-Wei, et al.
Published: (2026)

Hierarchical Motion Planning and Control under Unknown Nonlinear Dynamics via Predicted Reachability
by: Zhang, Zhiquan, et al.
Published: (2026)

Safe and Stable Neural Network Dynamical Systems for Robot Motion Planning
by: Binny, Allen Emmanuel, et al.
Published: (2025)

Interval Markov Decision Processes with Continuous Action-Spaces
by: Delimpaltadakis, Giannis, et al.
Published: (2022)

Safe and Dynamically-Feasible Motion Planning using Control Lyapunov and Barrier Functions
by: Mestres, Pol, et al.
Published: (2024)

Probabilistic Recursively Feasible Motion Planning Under Uncertain Environments
by: Sung, Hyeontae, et al.
Published: (2026)

Data-Driven Robust Optimization for Energy-Aware Safe Motion Planning of Electric Vehicles
by: Kumari, Simran, et al.
Published: (2023)

Disturbance Compensation for Safe Kinematic Control of Robotic Systems with Closed Architecture
by: Zhang, Fan, et al.
Published: (2025)

Efficiency through Uncertainty: Scalable Formal Synthesis for Stochastic Hybrid Systems
by: Cauchi, Nathalie, et al.
Published: (2019)

Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
by: Ahmadi, Sajad, et al.
Published: (2025)

Stochastic Barrier Certificates in the Presence of Dynamic Obstacles
by: Mazouz, Rayan, et al.
Published: (2026)