6 papers
Adaptive MPPI with Online Disturbance Covariance Estimation: Provable Stability Tightening via Spatial Smoothing
Hyung-Jin Yoon, Hunmin Kim
We study Model Predictive Path Integral (MPPI) control for nonlinear systems with additive process disturbances whose covariance is unknown, spatially varying, and slowly time-vary…
Residual-Conservative Model Predictive Path Integral Control
Hyung-Jin Yoon, Hunmin Kim
Sampling-based model predictive control methods handle nonlinear dynamics and complex cost landscapes through Monte Carlo rollouts, yet typically employ fixed constraint penalties…
Stochastic Stability of Nonlinear MPPI via Contraction Theory and Control Lyapunov Functions
Hyung-Jin Yoon, Hunmin Kim
Model Predictive Path Integral (MPPI) control is directly implementable on nonlinear systems because its online update requires only forward rollouts of the dynamics, not gradients…
Finite Reliability Representations: Noise-Calibrated Belief-Space Covers for Reliable Decision-Making
Hyung-Jin Yoon, Hunmin Kim
Physical sensing and actuation noise floors should inform how much belief resolution a decision-making system can reliably use. We introduce Finite Reliability Representations (FRR…
Finite-Sample Closed-Loop Stability of Model Predictive Path Integral Control for Linear Time-Invariant Systems
Hyung-Jin Yoon, Hunmin Kim
We establish finite-sample closed-loop stability guarantees for Model Predictive Path Integral (MPPI) control applied to discrete-time Linear Time-Invariant (LTI) systems with addi…
Synergistic Simplex: Cooperative Runtime Assurance for Safety-Critical Autonomous Systems
Ayoosh Bansal, Mikael Yeghiazaryan, Artyom Khachatryan +4
Autonomous systems increasingly rely on machine-learning (ML) components for safety-critical tasks such as perception and control in autonomous vehicles (AVs). While ML enables ess…