Suhan Park

Principal Investigator

Suhan Park박수한

Assistant Professor, Department of Robotics, Kwangwoon University

DREAM Lab. (Dynamic Robotic Embodiment & Autonomous Manipulation Lab.) Principal Investigator (PI)

Email park94@kw.ac.kr

Suhan Park is the Principal Investigator (PI) of DREAM Lab. (Dynamic Robotic Embodiment & Autonomous Manipulation Lab.) and Assistant Professor in the Department of Robotics at Kwangwoon University. The lab is located at #639 Hwado-gwan, 20 Gwangun-ro, Nowon-gu, Seoul, Korea, and the email address is park94@kw.ac.kr.

Name
Suhan Park (박수한)
Position
Assistant Professor
Role
Principal Investigator (PI), DREAM Lab. (Dynamic Robotic Embodiment & Autonomous Manipulation Lab.)
Affiliation
Department of Robotics, Kwangwoon University
Email
park94@kw.ac.kr
Office
#639 Hwado-gwan, 20 Gwangun-ro, Nowon-gu, Seoul, Korea
Lab website
https://drl.kw.ac.kr/

Research Interests

  • Robot Task and Motion Planning
  • Robot Intelligence
  • Embodied AI

Education

  • 2017 – 2024Ph.D., Dept. of Transdisciplinary Studies, Seoul National University (Advisor: Prof. Jaeheung Park)
  • 2013 – 2017B.S., Robotics, Kwangwoon University (Achievement Award)

Experience

  • 2025 –Assistant Professor, Department of Robotics, Kwangwoon University
  • 2024 – 2025Staff Engineer, Samsung Electronics

Activities

  • Associate Editor, IEEE International Conference on Robotics and Automation (ICRA)
  • Associate Editor, Journal of Mechanical Science and Technology
  • Robotics Bootcamp (Linux, ROS, and dynamic simulator lectures)
  • Alumnus of RO:BIT, Kwangwoon University robot game team

Selected Publications

  • PATACON: GPU-Parallel Tangent-Bundle RRT-Connect for Constrained Motion Planning Preprint 2026Project
  • LiPo: A Lightweight Post-optimization Framework for Smoothing Action Chunks Generated by Learned Policies IJCAS 2025Paper
  • A Constrained Motion Planning Method Exploiting Learned Latent Space for High-Dimensional State and Constraint Spaces IEEE/ASME T-MECH 2024Paper
  • Scalable Learned Geometric Feasibility for Cooperative Grasp and Motion Planning IEEE RA-L 2022Paper

All publications

All members