7 citations · 28 across the 31 of their papers we have counts for
34 papers
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…
An Information-Theoretic Analysis of Discrete-Time Control and Filtering Limitations by the I-MMSE Relationships
Neng Wan, Dapeng Li, Naira Hovakimyan +1
Fundamental limitations or performance trade-offs/limits are important properties and constraints of both control and filtering systems. Among various trade-off metrics, total info…
Learning When to Use Adaptive Adversarial Image Perturbations against Autonomous Vehicles
Hyung-Jin Yoon, Hamidreza Jafarnejadsani, Petros Voulgaris
The deep neural network (DNN) models for object detection using camera images are widely adopted in autonomous vehicles. However, DNN models are shown to be susceptible to adversar…
Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Data
Hyung-Jin Yoon, Petros Voulgaris
Due to recent climate changes, we have seen more frequent and severe wildfires in the United States. Predicting wildfires is critical for natural disaster prevention and mitigation…
Distributed Primal-dual Optimization for Heterogeneous Multi-agent Systems
Yichuan Li, Petros Voulgaris, Nikolaos M. Freris
Heterogeneous networks comprise agents with varying capabilities in terms of computation, storage, and communication. In such settings, it is crucial to factor in the operating cha…
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.…
Communication Efficient Curvature Aided Primal-dual Algorithms for Decentralized Optimization
Yichuan Li, Petros G. Voulgaris, Dusan M. Stipanovic +1
This paper presents a family of algorithms for decentralized convex composite problems. We consider the setting of a network of agents that cooperatively minimize a global objectiv…
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…
A Communication Efficient Quasi-Newton Method for Large-scale Distributed Multi-agent Optimization
Yichuan Li, Petros G. Voulgaris, Nikolaos M. Freris
We propose a communication efficient quasi-Newton method for large-scale multi-agent convex composite optimization. We assume the setting of a network of agents that cooperatively…
Learning Wildfire Model from Incomplete State Observations
Alissa Chavalithumrong, Hyung-Jin Yoon, Petros Voulgaris
As wildfires are expected to become more frequent and severe, improved prediction models are vital to mitigating risk and allocating resources. With remote sensing data, valuable s…
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…
Accelerated Almost-Sure Convergence Rates for Nonconvex Stochastic Gradient Descent using Stochastic Learning Rates
Theodoros Mamalis, Dusan Stipanovic, Petros Voulgaris
Large-scale optimization problems require algorithms both effective and efficient. One such popular and proven algorithm is Stochastic Gradient Descent which uses first-order gradi…
Stochastic Learning Rate Optimization in the Stochastic Approximation and Online Learning Settings
Theodoros Mamalis, Dusan Stipanovic, Petros Voulgaris
In this work, multiplicative stochasticity is applied to the learning rate of stochastic optimization algorithms, giving rise to stochastic learning-rate schemes. In-expectation th…
BFGS-ADMM for Large-Scale Distributed Optimization
Yichuan Li, Yonghai Gong, Nikolaos M. Freris +2
We consider a class of distributed optimization problem where the objective function consists of a sum of strongly convex and smooth functions and a (possibly nonsmooth) convex reg…
DN-ADMM: Distributed Newton ADMM for Multi-agent Optimization
Yichuan Li, Nikolaos M. Freris, Petros Voulgaris +1
In a multi-agent network, we consider the problem of minimizing an objective function that is expressed as the sum of private convex and smooth functions, and a (possibly) non-diff…
Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies
Hyungsoo Kang, Hyung-Jin Yoon, Venanzio Cichella +2
This paper presents a time-coordination algorithm for multiple UAVs executing cooperative missions. Unlike previous algorithms, it does not rely on the assumption that the communic…
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…
Learning Image Attacks toward Vision Guided Autonomous Vehicles
Hyung-Jin Yoon, Hamidreza Jafarnejadsani, Petros Voulgaris
While adversarial neural networks have been shown successful for static image attacks, very few approaches have been developed for attacking online image streams while taking into…
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…
Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems
Neng Wan, Aditya Gahlawat, Naira Hovakimyan +2
Distributed algorithms for both discrete-time and continuous-time linearly solvable optimal control (LSOC) problems of networked multi-agent systems (MASs) are investigated in this…
Finite-Time Model Inference From A Single Noisy Trajectory
Yanbing Mao, Naira Hovakimyan, Petros Voulgaris +1
This paper proposes a novel model inference procedure to identify system matrix from a single noisy trajectory over a finite-time interval. The proposed inference procedure compris…
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…
Cooperative Path Integral Control for Stochastic Multi-Agent Systems
Neng Wan, Aditya Gahlawat, Naira Hovakimyan +2
A distributed stochastic optimal control solution is presented for cooperative multi-agent systems. The network of agents is partitioned into multiple factorial subsystems, each of…