activity
20122026
most citedExperimental Validation of Linear and Nonlinear MPC on an Articulated Unmanned Ground Vehicle

102 citations · 204 across the 60 of their papers we have counts for

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Showing 2023Show all

9 papers · 1 filter

eess.SY2023

Control-Based Planning over Probability Mass Function Measurements via Robust Linear Programming

Mehdi Kermanshah, Calin Belta, Roberto Tron

We propose an approach to synthesize linear feedback controllers for linear systems in polygonal environments. Our method focuses on designing a robust controller that can account…

math.OC2023

Feasibility-Guaranteed Safety-Critical Control with Applications to Heterogeneous Platoons

Shuo Liu, Wei Xiao, Calin A. Belta

This paper studies safety and feasibility guarantees for systems with tight control bounds. It has been shown that stabilizing an affine control system while optimizing a quadratic…

cs.FL2023

Robustness Measures and Monitors for Time Window Temporal Logic

Ahmad Ahmad, Cristian-Ioan Vasile, Roberto Tron +1

Temporal logics (TLs) have been widely used to formalize interpretable tasks for cyber-physical systems. Time Window Temporal Logic (TWTL) has been recently proposed as a specifica…

eess.SY2023

Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNet

Wenliang Liu, Wei Xiao, Calin Belta

In this paper, we consider the problem of learning a neural network controller for a system required to satisfy a Signal Temporal Logic (STL) specification. We exploit STL quantita…

eess.SY2023

Uncertainty Quantification for Recursive Estimation in Adaptive Safety-Critical Control

Max H. Cohen, Makai Mann, Kevin Leahy +1

In this paper, we present a framework for online parameter estimation and uncertainty quantification in the context of adaptive safety-critical control. The key insight enabling ou…

cs.RO2023

LQR-CBF-RRT*: Safe and Optimal Motion Planning

Guang Yang, Mingyu Cai, Ahmad Ahmad +3

We present LQR-CBF-RRT*, an incremental sampling-based algorithm for offline motion planning. Our framework leverages the strength of Control Barrier Functions (CBFs) and Linear Qu…