Decoding human motion intention from surface EMG (sEMG) to enable intuitive and adaptive robot control.
표면 근전도(sEMG) 신호로 사람의 움직임 의도를 파악하여 직관적이고 적응적인 로봇 제어를 구현합니다.
sEMG-based motion intention recognition
Robust muscle activation estimation under fatigue and electrode shift
Adaptive control strategies for human-in-the-loop robotic systems
Experimental validation with real-time robotic platforms
Developing safe, efficient, and intuitive ways for humans and robots to work together.
인간과 로봇이 안전하고 효율적이며 직관적으로 협업할 수 있는 방법을 연구합니다.
Shared control frameworks for collaborative tasks
Human workload and muscle fatigue assessment
Safety-aware interaction in shared workspaces
Evaluation of task efficiency and user experience
Designing biosignal-driven wearable systems that physically support and augment people.
생체신호 기반 웨어러블 시스템으로 사람의 신체 활동을 보조하고 능력을 확장합니다.
Wearable robotic interfaces using biosignals
Assistive control strategies for physical support
Human-centered design for comfort and usability
Integration of soft robotics and sensing technologies
Building autonomous, adaptive robots and intuitive teleoperation with Vision-Language-Action (VLA) models and reinforcement learning.
VLA 모델과 강화학습을 활용해 자율적이고 적응적인 지능형 로봇과 직관적인 원격 조작 시스템을 개발합니다.
VLA models for language-guided robot manipulation
Reinforcement learning for legged and whole-body mobile manipulation
Sim-to-real transfer and real-world validation
Biosignal-integrated teleoperation with predictive models
Designing and building custom robotic hardware, from mechanisms and actuators to embedded sensing, for our research platforms.
연구에 필요한 로봇 하드웨어를 메커니즘·구동기 설계부터 센서 통합까지 직접 설계하고 제작합니다.
Mechanism and actuator design for robotic arms and hands
Prototyping of wearable devices and soft robotic components
Embedded sensing and biosignal acquisition hardware
Rapid prototyping with CAD, 3D printing, and custom PCBs