4 papers · 1 filter
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…