Youngjin Seo

I'm an Integrated M.S./Ph.D. student and the student lab leader of the Robotics and Intelligent System Engineering Lab (RISE Lab) at Sungkyunkwan University (SKKU), advised by Prof. Hyungpil Moon.

I'm interested in robot learning for manipulation, with a focus on imitation learning, vision-language-action (VLA) models, and force-based policies.

Email / CV (coming soon) / Scholar / Github

Education

Sungkyunkwan University (SKKU), South Korea
Integrated M.S./Ph.D., Intelligent Robotics
Mar. 2025 – present
Sungkyunkwan University (SKKU), South Korea
B.S., Mechanical Engineering (summa cum laude, top 5%)
Mar. 2019 – Feb. 2025

Publications

	EquiGQNet: Fast Grasp Quality Evaluation via Shared Equivariant Point Cloud Encoding Sungwon Seo, Jaeseog Won, Jiyou Shin, Youngjin Seo, Hyunjun Kim, Seokmin Yoon, Tuan Luong, Hyungpil Moon arXiv, 2026 project page / arXiv A 6-DoF grasp quality evaluator that replaces per-candidate re-encoding with an SO(3)-equivariant encode-once-then-rotate scheme, reusing a shared scene encoding while keeping grasp-relative local geometry.
	URF: A Unified Robot Control-Policy Framework for Stable Contact Aware Manipulation Jiyou Shin, Youngjin Seo, Jaeseog Won, Sungwon Seo, Hyunjun Kim, Seokmin Yoon, Tuan Luong, Hyungpil Moon arXiv, 2026 project page / arXiv A manipulation policy that predicts not only a compliant action but also the controller behavior used to execute it, jointly outputting a virtual target, a stiffness matrix, and an impedance-admittance switch ratio.
	Benchmarking 6D Pose Estimation and 6-DoF Grasp Detection on a Low-Power NPU: Case Studies with PVN3D and HGGD Youngjin Seo, Hyojun Yun, Hong-ryul Jung, Hyungpil Moon (* equal contribution) International Conference on Control, Automation and Systems (ICCAS), 2025 paper A benchmark of PVN3D and HGGD on a low-power NPU, measuring whether 6D pose estimation and 6-DoF grasp detection stay practical under embedded compute budgets.

Projects

Empowering Legged Robots with Multimodal Mapping and Localization for Industrial Environments
Aug. 2026 – present

Development of a K-Logistics Humanoid Robot Integrated with a High-Sensitivity Robotic Hand Based on a Multimodal AI Foundation Model
Sep. 2025 – Sep. 2026

Deployed imitation learning and vision-language-action algorithms, including ACT, π₀, π_0.5, and TA-VLA
Set up an Isaac Sim simulation environment with a dexterous hand for demonstration data augmentation

Development of a SLAM-Based Drone System for Cart Monitoring
Apr. 2026 – Aug. 2026

Implemented an integrated ground control interface that visualizes real-time drone and cart positions on a 2D map
Enabled drone waypoint setting and cart position correction directly through mouse interaction on the map

Development of Core Technology for Mobile Manipulator for 5G Edge-Based Transportation and Manipulation
Jun. 2025 – Dec. 2025

Object recognition using YOLO11, SAM 2, and FoundationPose
Grasp point detection with HGGD, including collision checking of the detected grasps
System integration for grasping with a three-fingered hand

Development of Low-Cost, High-Performance Visual Sensor Technology Integrated with AI Semiconductors and AI Algorithms Designed for Robots
Dec. 2024 – Nov. 2025

Converted the architectures of PVN3D and HGGD to run on an NPU

Development of a Simulation Drone Competition Utilizing Realistic Environments and Drone Dynamics
Mar. 2023 – Dec. 2023

Developed a multi-drone racing competition in an Unreal Engine simulation environment using AirSim, PX4, and QGroundControl
Built an autonomous drone flight algorithm based on PID control within the simulation environment

Teaching

AI & Robotics Practical Training for Vocational High School Students
Instructor, Sungkyunkwan University
Jul. 2026
Kinematics of Machinery (EME3017)
Teaching Assistant, Sungkyunkwan University
Spring 2025
Design Lab on Vibration and Dynamic Systems (EME3057)
Teaching Assistant, Sungkyunkwan University
Spring 2025

Feel free to reach out at soh2879 [at] g.skku.edu for any questions.

Template from Jon Barron's website.