M.S. student @ Yonsei University.
I am currently a M.S. student at Machine Learning and Control Systems Lab (MLCS) at Yonsei University, advised by Prof. Jongeun Choi. My research interests lie in Robotics and Machine Learning, with a particular focus on leveraging diffusion models and geometric deep learning in robot learning.
I received my Bachelor’s degree in Mechanical Engineering from Yonsei University.
M.S. in Mechanical Engineering, 2024.03 ~ present
Yonsei University
B.S. in Mechanical Engineering, 2018.03 ~ 2024.02
Yonsei University
Diffusion models have risen as a powerful tool in robotics due to their flexibility and multi-modality. While some of these methods effectively address complex problems, they often depend heavily on inference-time obstacle detection and require additional equipment. Addressing these challenges, we present a method that, during inference time, simultaneously generates only reachable goals and plans motions that avoid obstacles, all from a single visual input. Central to our approach is the novel use of a collision-avoiding diffusion kernel for training. Through evaluations against behavior-cloning and classical diffusion models, our framework has proven its robustness. It is particularly effective in multi-modal environments, navigating toward goals and avoiding unreachable ones blocked by obstacles, while ensuring collision avoidance.