10 papers
Provably Safe Stein Variational Clarity-Aware Informative Planning
Kaleb Ben Naveed, Utkrisht Sahai, Anouck Girard +1
Autonomous robots are increasingly deployed for information-gathering tasks in environments that vary across space and time. Planning informative and safe trajectories in such sett…
Time Shift Governor-Guided MPC with Collision Cone CBFs for Safe Adaptive Cruise Control in Dynamic Environments
Robin Inho Kee, Taehyeun Kim, Anouck Girard +1
This paper introduces a Time Shift Governor (TSG)-guided Model Predictive Controller with Control Barrier Functions (CBFs)-based constraints for adaptive cruise control (ACC). This…
Control Invariant Sets for Neural Network Dynamical Systems and Recursive Feasibility in Model Predictive Control
Xiao Li, Tianhao Wei, Changliu Liu +2
Neural networks are powerful tools for data-driven modeling of complex dynamical systems, enhancing predictive capability for control applications. However, their inherent nonlinea…
Learning Hamiltonian Dynamics with Bayesian Data Assimilation
Taehyeun Kim, Tae-Geun Kim, Anouck Girard +1
In this paper, we develop a neural network-based approach for time-series prediction in unknown Hamiltonian dynamical systems. Our approach leverages a surrogate model and learns t…
Constrained Control for Autonomous Spacecraft Rendezvous: Learning-Based Time Shift Governor
Taehyeun Kim, Robin Inho Kee, Ilya Kolmanovsky +1
This paper develops a Time Shift Governor (TSG)-based control scheme to enforce constraints during rendezvous and docking (RD) missions in the setting of the Two-Body problem. As a…
CIKAN: Constraint Informed Kolmogorov-Arnold Networks for Autonomous Spacecraft Rendezvous using Time Shift Governor
Taehyeun Kim, Anouck Girard, Ilya Kolmanovsky
The paper considers a Constrained-Informed Neural Network (CINN) approximation for the Time Shift Governor (TSG), which is an add-on scheme to the nominal closed-loop system used t…
Safe Adaptive Cruise Control Under Perception Uncertainty: A Deep Ensemble and Conformal Tube Model Predictive Control Approach
Xiao Li, Anouck Girard, Ilya Kolmanovsky
Autonomous driving heavily relies on perception systems to interpret the environment for decision-making. To enhance robustness in these safety critical applications, this paper co…
Time Shift Governor for Constrained Control of Spacecraft Orbit and Attitude Relative Motion in Bicircular Restricted Four-Body Problem
Taehyeun Kim, Ilya Kolmanovsky, Anouck Girard
This paper considers constrained spacecraft rendezvous and docking (RVD) in the setting of the Bicircular Restricted Four-Body Problem (BCR4BP), while accounting for attitude dynam…
Autonomous Driving With Perception Uncertainties: Deep-Ensemble Based Adaptive Cruise Control
Xiao Li, H. Eric Tseng, Anouck Girard +1
Autonomous driving depends on perception systems to understand the environment and to inform downstream decision-making. While advanced perception systems utilizing black-box Deep…
System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models
Xiao Li, Yutong Li, Anouck Girard +1
The Neural Network (NN), as a black-box function approximator, has been considered in many control and robotics applications. However, difficulties in verifying the overall system…