51 citations · 164 across the 35 of their papers we have counts for
13 papers · 1 filter
Rapid Uncertainty Propagation and Chance-Constrained Path Planning for Small Unmanned Aerial Vehicles
Andrew W. Berning, Anouck Girard, Ilya Kolmanovsky +1
With the number of small Unmanned Aircraft Systems (sUAS) in the national airspace projected to increase in the next few years, there is growing interest in a traffic management sy…
A Novel Approach for Optimal Trajectory Design with Multiple Operation Modes of Propulsion System, Part 2
Ehsan Taheri, John L. Junkins, Ilya Kolmanovsky +1
Equipping a spacecraft with multiple solar-powered electric engines (of the same or different types) compounds the task of optimal trajectory design due to presence of both real-va…
A Novel Approach for Optimal Trajectory Design with Multiple Operation Modes of Propulsion System, Part 1
Ehsan Taheri, John L. Junkins, Ilya Kolmanovsky +1
Efficient performance of a number of engineering systems is achieved through different modes of operation - yielding systems described as "hybrid", containing both real-valued and…
Spacecraft Relative Motion Planning Using Chained Chance-Constrained Admissible Sets
Andrew W. Berning, Nan I. Li, Anouck Girard +3
With the increasing interest in proximity and docking operations, there is a growing interest in spacecraft relative motion control. This paper extends a previously proposed constr…
Co-optimization of Speed and Gearshift Control for Battery Electric Vehicles Using Preview Information
Kyoungseok Han, Nan Li, Ilya Kolmanovsky +4
This paper addresses the co-optimization of speed and gearshift control for battery electric vehicles using short-range traffic information. To achieve greater electric motor effic…
Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving
Ali Baheri, Subramanya Nageshrao, H. Eric Tseng +3
In this paper, we present a safe deep reinforcement learning system for automated driving. The proposed framework leverages merits of both rule-based and learning-based approaches…
Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
Ran Tian, Nan Li, Ilya Kolmanovsky +2
For a foreseeable future, autonomous vehicles (AVs) will operate in traffic together with human-driven vehicles. Their planning and control systems need extensive testing, includin…
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control
Sisi Li, Nan Li, Anouck Girard +1
In this paper, we describe an integrated framework for autonomous decision making in a dynamic and interactive environment. We model the interactions between the ego agent and its…
Beating humans in a penny-matching game by leveraging cognitive hierarchy theory and Bayesian learning
Ran Tian, Nan Li, Ilya Kolmanovsky +1
It is a long-standing goal of artificial intelligence (AI) to be superior to human beings in decision making. Games are suitable for testing AI capabilities of making good decision…
A Reference Governor for Nonlinear Systems with Disturbance Inputs Based on Logarithmic Norms and Quadratic Programming
Nan Li, Ilya Kolmanovsky, Anouck Girard
This note describes a reference governor design for a continuous-time nonlinear system with an additive disturbance. The design is based on predicting the response of the nonlinear…
Detection-averse optimal and receding-horizon control for Markov decision processes
Nan Li, Ilya Kolmanovsky, Anouck Girard
In this paper, we consider a Markov decision process (MDP), where the ego agent has a nominal objective to pursue while needs to hide its state from detection by an adversary. Afte…
Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
Nan Li, Yu Yao, Ilya Kolmanovsky +2
Motivated by the need to develop simulation tools for verification and validation of autonomous driving systems operating in traffic consisting of both autonomous and human-driven…
An analytical safe approximation to joint chance-constrained programming with additive Gaussian noises
Nan Li, Ilya Kolmanovsky, Anouck Girard
We propose a safe approximation to joint chance-constrained programming where the constraint functions are additively dependent on a normally-distributed random vector. The approxi…