Watch experiment ↗01Locomotion and loco-manipulation
Humanoid Control
- Locomotion
- Whole-body motion
- Physical AI
OPEN POSITIONSRCI Lab is recruiting motivated undergraduate researchers and graduate students.
Recruitment details →ROBOT CONTROL · PHYSICAL AI · INTELLIGENCE
We build control and intelligence that help robots move, collaborate, and make decisions in complex, human-centered environments.
WHAT WE DO
From optimal control to Physical AI, our work connects rigorous methods with experiments on real robotic systems.
Watch experiment ↗01Locomotion and loco-manipulation
Watch experiment ↗02Dynamic coordination for complex robots
Watch experiment ↗03Real-time decisions under constraints
Watch experiment ↗04Planning on complex constraint manifolds
Watch experiment ↗05Language-guided robot behavior
06Semantic maps for embodied navigation
SELECTED WORK
Research across robot control, motion planning, navigation, and learning-enabled robotic systems.
Browse publications →LAB UPDATES
Through the program, all lab members receive premium (Max) Claude access for research, coding, and writing.
과제명: 시뮬레이션 상 모바일 로봇 탑재 매니퓰레이터 모션 및 제어 개발 · 과제형태: 산학협력 · 지원기관: 모빈 · 수행기간: 2026
Thanh Nguyen Truong, Sanghyun Kim†, “High-Performance Fixed-Time Active Fault-Tolerant Control of Robotic Manipulators via Sparse Physics-Informed Dynamics Learning,” Information Sciences, 2026.
과제명: 자율 공정을 위한 모션 플래닝 기술 개발 · 과제형태: 산학협력 · 지원기관: PIE Robotics · 수행기간: 2026
과제명: 화학 실험 자동화를 위한 VLM 기반 제어 기술 개발 · 과제형태: 산학협력 · 지원기관: 카이로스랩 · 수행기간: 2026
과제명: 휴머노이드 교육 자문 용역 · 과제형태: 산학협력 · 지원기관: 이앤오즈 · 수행기간: 2026
과제명: 화물하역작업을 위한 모션플래닝 알고리즘의 개발 · 과제형태: 산학협력 · 지원기관: 로보에 테크놀로지 · 수행기간: 2026
Jiho Hong*, Eunae Kang*, Sanghyun Kim†, Young-Sik Shin†, “Instance-Enriched Semantic Maps for Visual Language Navigation,” Engineering Applications of Artificial Intelligence, 2026.