1 citations · 1 across the 3 of their papers we have counts for
6 papers
Decoupled Continuous-Time Reinforcement Learning via Hamiltonian Flow
Minh Nguyen
Many real-world control problems, ranging from finance to robotics, evolve in continuous time with non-uniform, event-driven decisions. Standard discrete-time reinforcement learnin…
Scaling Single Human Demonstrations for Imitation Learning using Generative Foundational Models
Nick Heppert, Minh Quang Nguyen, Abhinav Valada
Imitation learning is a popular paradigm to teach robots new tasks, but collecting robot demonstrations through teleoperation or kinesthetic teaching is tedious and time-consuming.…
GRL-SNAM: Geometric Reinforcement Learning with Path Differential Hamiltonians for Simultaneous Navigation and Mapping in Unknown Environments
Aditya Sai Ellendula, Yi Wang, Minh Nguyen +1
We present GRL-SNAM, a geometric reinforcement learning framework for Simultaneous Navigation and Mapping(SNAM) in unknown environments. A SNAM problem is challenging as it needs t…
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
Luke McLennan, Yi Wang, Ryan Farell +2
We introduce a robust framework for learning various generalized Hamiltonian dynamics from noisy, sparse phase-space data and in an unsupervised manner based on variational Bayesia…
Decentralized Navigation of a Cable-Towed Load using Quadrupedal Robot Team via MARL
Wen-Tse Chen, Minh Nguyen, Zhongyu Li +2
This work addresses the challenge of enabling a team of quadrupedal robots to collaboratively tow a cable-connected load through cluttered and unstructured environments while avoid…
Low-cost Robust Night-time Aerial Material Segmentation through Hyperspectral Data and Sparse Spatio-Temporal Learning
Chandrajit Bajaj, Minh Nguyen, Shubham Bhardwaj
Material segmentation is a complex task, particularly when dealing with aerial data in poor lighting and atmospheric conditions. To address this, hyperspectral data from specialize…