16 citations · 66 across the 30 of their papers we have counts for
31 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…
Addressing Behavior Model Inaccuracies for Safe Motion Control in Uncertain Dynamic Environments
Minjun Sung, Hunmin Kim, Naira Hovakimyan
Uncertainties in the environment and behavior model inaccuracies compromise the state estimation of a dynamic obstacle and its trajectory predictions, introducing biases in estimat…
Resilient Estimator-based Control Barrier Functions for Dynamical Systems with Disturbances and Noise
Chuyuan Tao, Wenbin Wan, Junjie Gao +3
Control Barrier Function (CBF) is an emerging method that guarantees safety in path planning problems by generating a control command to ensure the forward invariance of a safety s…
Synergistic Perception and Control Simplex for Verifiable Safe Vertical Landing
Ayoosh Bansal, Yang Zhao, James Zhu +6
Perception, Planning, and Control form the essential components of autonomy in advanced air mobility. This work advances the holistic integration of these components to enhance the…
Backup Plan Constrained Model Predictive Control with Guaranteed Stability
Ran Tao, Hunmin Kim, Hyung-Jin Yoon +4
This article proposes and evaluates a new safety concept called backup plan safety for path planning of autonomous vehicles under mission uncertainty using model predictive control…
Certified Robust Control under Adversarial Perturbations
Jinghan Yang, Hunmin Kim, Wenbin Wan +2
Autonomous systems increasingly rely on machine learning techniques to transform high-dimensional raw inputs into predictions that are then used for decision-making and control. Ho…
RRT Guided Model Predictive Path Integral Method
Chuyuan Tao, Hunmin Kim, Naira Hovakimyan
This work presents an optimal sampling-based method to solve the real-time motion planning problem in static and dynamic environments, exploiting the Rapid-exploring Random Trees (…
Perception Simplex: Verifiable Collision Avoidance in Autonomous Vehicles Amidst Obstacle Detection Faults
Ayoosh Bansal, Hunmin Kim, Simon Yu +4
Advances in deep learning have revolutionized cyber-physical applications, including the development of Autonomous Vehicles. However, real-world collisions involving autonomous con…
Verifiable Obstacle Detection
Ayoosh Bansal, Hunmin Kim, Simon Yu +4
Perception of obstacles remains a critical safety concern for autonomous vehicles. Real-world collisions have shown that the autonomy faults leading to fatal collisions originate f…
Path Integral Methods with Stochastic Control Barrier Functions
Chuyuan Tao, Hyung-Jin Yoon, Hunmin Kim +2
Safe control designs for robotic systems remain challenging because of the difficulties of explicitly solving optimal control with nonlinear dynamics perturbed by stochastic noise.…
Sampling Complexity of Path Integral Methods for Trajectory Optimization
Hyung-Jin Yoon, Chuyuan Tao, Hunmin Kim +2
The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random tra…
Protective Mission against a Highly Maneuverable Rogue Drone Using Defense Margin Strategy
Minjun Sung, Christophe Johannes Hiltebrandt-McIntosh, Hunmin Kim +1
The current paper studies a protective mission to defend a domain called the safe zone from a rogue drone invasion. We consider a one attacker and one defender drone scenario where…
Control Barrier Function Augmentation in Sampling-based Control Algorithm for Sample Efficiency
Chuyuan Tao, Hunmin Kim, Hyungjin Yoon +2
For a nonlinear stochastic path planning problem, sampling-based algorithms generate thousands of random sample trajectories to find the optimal path while guaranteeing safety by L…
Constrained Attack-Resilient Estimation of Stochastic Cyber-Physical Systems
Wenbin Wan, Hunmin Kim, Naira Hovakimyan +1
In this paper, a constrained attack-resilient estimation algorithm (CARE) is developed for stochastic cyber-physical systems. The proposed CARE can simultaneously estimate the comp…
Backup Plan Constrained Model Predictive Control
Hunmin Kim, Hyungjin Yoon, Wenbin Wan +3
This article proposes a new safety concept: backup plan safety. The backup plan safety is defined as the ability to complete one of the alternative missions in the case of primary…
Estimation and Planning of Exploration Over Grid Map Using A Spatiotemporal Model with Incomplete State Observations
Hyung-Jin Yoon, Hunmin Kim, Kripash Shrestha +2
Path planning over spatiotemporal models can be applied to a variety of applications such as UAVs searching for spreading wildfire in mountains or network of balloons in time-varyi…
Robust Vehicle Lane Keeping Control with Networked Proactive Adaptation
Hunmin Kim, Wenbin Wan, Naira Hovakimyan +2
Road condition is an important environmental factor for autonomous vehicle control. A dramatic change in the road condition from the nominal status is a source of uncertainty that…
Safety Constrained Multi-UAV Time Coordination: A Bi-level Control Framework in GPS Denied Environment
Wenbin Wan, Hunmin Kim, Yikun Cheng +3
Unmanned aerial vehicles (UAVs) suffer from sensor drifts in GPS denied environments, which can cause safety issues. To avoid intolerable sensor drifts while completing the time-cr…
A Safety Constrained Control Framework for UAVs in GPS Denied Environment
Wenbin Wan, Hunmin Kim, Naira Hovakimyan +2
Unmanned aerial vehicles (UAVs) suffer from sensor drifts in GPS denied environments, which can lead to potentially dangerous situations. To avoid intolerable sensor drifts in the…