9 citations · 18 across the 4 of their papers we have counts for
9 papers
Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks
Yifang Liu, Diego Romeres, Devesh K. Jha +1
One of the main challenges in peg-in-a-hole (PiH) insertion tasks is in handling the uncertainty in the location of the target hole. In order to address it, high-dimensional sensor…
A Holistic Framework for Parameter Coordination of Interconnected Microgrids against Disasters
Tong Huang, Hongbo Sun, Kyeong Jin Kim +2
This paper proposes a holistic framework for parameter coordination of a power electronic-interfaced microgrid interconnection against natural disasters. The paper identifies a tra…
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh K. Jha +2
Deep reinforcement learning (RL) algorithms have recently achieved remarkable successes in various sequential decision making tasks, leveraging advances in methods for training lar…
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements
Alberto Dalla Libera, Diego Romeres, Devesh K. Jha +2
In this paper, we propose a derivative-free model learning framework for Reinforcement Learning (RL) algorithms based on Gaussian Process Regression (GPR). In many mechanical syste…
Multi-label Prediction in Time Series Data using Deep Neural Networks
Wenyu Zhang, Devesh K. Jha, Emil Laftchiev +1
This paper addresses a multi-label predictive fault classification problem for multidimensional time-series data. While fault (event) detection problems have been thoroughly studie…
Local Policy Optimization for Trajectory-Centric Reinforcement Learning
Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan +4
The goal of this paper is to present a method for simultaneous trajectory and local stabilizing policy optimization to generate local policies for trajectory-centric model-based re…