9 citations · 21 across the 5 of their papers we have counts for
7 papers
Effect of Human Involvement on Work Performance and Fluency in Human-Robot Collaboration for Recycling
Sruthi Ramadurai, Heejin Jeong
Human-robot collaboration has significant potential in recycling due to the wide variation in the composition of recyclable products. Six participants performed a recyclable item s…
Effects of Head-locked Augmented Reality on User's performance and perceived workload
Yalda Ghasemi, Ankit Singh, Myunghee Kim +2
An augmented reality (AR) environment includes a set of digital elements with which the users interact while performing certain tasks. Recent AR head-mounted displays allow users t…
Model-based Task Analysis and Large-scale Video-based Remote Evaluation Methods for Extended Reality Research
Yalda Ghasemi, Heejin Jeong
In this paper, we introduce two remote extended reality (XR) research methods that can overcome the limitations of lab-based controlled experiments, especially during the COVID-19…
Scalable Reinforcement Learning Policies for Multi-Agent Control
Christopher D. Hsu, Heejin Jeong, George J. Pappas +1
We develop a Multi-Agent Reinforcement Learning (MARL) method to learn scalable control policies for target tracking. Our method can handle an arbitrary number of pursuers and targ…
Learning to Track Dynamic Targets in Partially Known Environments
Heejin Jeong, Hamed Hassani, Manfred Morari +2
We solve active target tracking, one of the essential tasks in autonomous systems, using a deep reinforcement learning (RL) approach. In this problem, an autonomous agent is tasked…
Learning Q-network for Active Information Acquisition
Heejin Jeong, Brent Schlotfeldt, Hamed Hassani +3
In this paper, we propose a novel Reinforcement Learning approach for solving the Active Information Acquisition problem, which requires an agent to choose a sequence of actions in…
Assumed Density Filtering Q-learning
Heejin Jeong, Clark Zhang, George J. Pappas +1
While off-policy temporal difference (TD) methods have widely been used in reinforcement learning due to their efficiency and simple implementation, their Bayesian counterparts hav…