Hyunyoung Jung

I am a second-year Master's student at Georgia Institute of Technology, majoring in Electrical and Computer Engineering. I am currently being advised by Dr. Sehoon Ha and closely working with Dr. Hae-Won Park.

I received my Bachelor's degree at Seoul National University where I majored in Mechanical Engineering and Computer Science and Engineering.

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Research

My research goal is to develop learning-based control algorithms that enable robust and agile locomotion and interactive behaviors within human environments. For this, I am currently working on research in legged robot locomotion, employing an approach that integrates classical control and learning-based methods. I believe this approach can complement the drawbacks of each method by reducing the burden of reward engineering and improving the performance of the model-based method. Furthermore, I am exploring the possibilities of human motion-driven control by establishing correspondence between humans and robots.

Publications and Preprints

We introduce a guided unsupervised reinforcement learning framework that simultaneously learns robot skills and their correspondence to human motions.

We propose a learning framework that can bridge between model-based and learning-based approaches for legged robot control by imitating expert model predictive control (MPC) and fine-tuning the pre-trained policy with reinforcement learning.

Ongoing Projects

Training the locomotion of full-sized humanoids is a challenging task and less investigated in a learning-based control society compared to quadrupedal robot locomotion. Unlike quadrupeds, the humanoids have more complicated structures making it hard to use a straightforward model-free reinforcement learning approach.
In this project, we address this issue by utilizing our established framework, IFM, to enhance the robustness of humanoid locomotion, specifically solving instability in the reinforcement learning stage.

Education

Georgia Institute of Technology

Seoul National University

Work and Teaching Experiences

CS 8803 Deep Reinforcment Learning for Intel. Control

CS 3451 Computer Graphics

Saige Research

Samsung Electronics