원정담 연구실

We are interested in exploring how deep learning can be leveraged to improve the quality and efficiency of the existing production process for character animation. Additionally, we aim to develop novel methods for generating character animation.

We are interested in simulating humans and creatures while adhering to the laws of physics. We develop diverse learning-based frameworks that utilize physics simulation and deep reinforcement learning to generate motions.

Our objective is to generate realistic and natural motions for users or autonomous avatars, specifically designed for Virtual Reality (VR) and Augmented Reality (AR) applications.

Modeling the skeletal structure, muscular system, and nervous system of humans and animals. We aim to gain a deeper understanding of the principles governing their movements and apply to medical applications.

Robot simulation and control are additional areas of interest for us. In particular, we focus on the design of controllers for quadruped robots to enable agile movements and exoskeletal robots.