103 citations · 191 across the 10 of their papers we have counts for
11 papers
Empirical Study of Dynamic Regret in Online Model Predictive Control for Linear Time-Varying Systems
Nhat M. Nguyen
Model Predictive Control (MPC) is a widely used technique for managing timevarying systems, supported by extensive theoretical analysis. While theoretical studies employing dynamic…
Real-Time Reconfiguration and Connectivity Maintenance for AUVs Network Under External Disturbances using Distributed Nonlinear Model Predictive Control
Nhat Minh Nguyen, Stephen McIlvanna, Jack Close +1
Advancements in underwater vehicle technology have significantly expanded the potential scope for deploying autonomous or remotely operated underwater vehicles in novel practical a…
A Twin Delayed Deep Deterministic Policy Gradient Algorithm for Autonomous Ground Vehicle Navigation via Digital Twin Perception Awareness
Kabirat Olayemi, Mien Van, Sean McLoone +4
Autonomous ground vehicle (UGV) navigation has the potential to revolutionize the transportation system by increasing accessibility to disabled people, ensure safety and convenienc…
Digital Twin-Driven Reinforcement Learning for Obstacle Avoidance in Robot Manipulators: A Self-Improving Online Training Framework
Yuzhu Sun, Mien Van, Stephen McIlvanna +4
The evolution and growing automation of collaborative robots introduce more complexity and unpredictability to systems, highlighting the crucial need for robot's adaptability and f…
Fixed-time Adaptive Neural Control for Physical Human-Robot Collaboration with Time-Varying Workspace Constraints
Yuzhu Sun, Mien Van, Stephen McIlvanna +4
Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a nov…
Differentiable Physics-based Greenhouse Simulation
Nhat M. Nguyen, Hieu T. Tran, Minh V. Duong +2
We present a differentiable greenhouse simulation model based on physical processes whose parameters can be obtained by training from real data. The physics-based simulation model…
Learning robust driving policies without online exploration
Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh +2
We propose a multi-time-scale predictive representation learning method to efficiently learn robust driving policies in an offline manner that generalize well to novel road geometr…
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella +34
Multi-agent interaction is a fundamental aspect of autonomous driving in the real world. Despite more than a decade of research and development, the problem of how to competently i…
Learning predictive representations in autonomous driving to improve deep reinforcement learning
Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh +1
Reinforcement learning using a novel predictive representation is applied to autonomous driving to accomplish the task of driving between lane markings where substantial benefits i…
Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans
Jun Jin, Nhat M. Nguyen, Nazmus Sakib +3
We propose a method to tackle the problem of mapless collision-avoidance navigation where humans are present using 2D laser scans. Our proposed method uses ego-safety to measure co…
Generative Adversarial Networks using Adaptive Convolution
Nhat M. Nguyen, Nilanjan Ray
Most existing GANs architectures that generate images use transposed convolution or resize-convolution as their upsampling algorithm from lower to higher resolution feature maps in…