Edge AI & Deployment
엣지 AI 및 배포
TensorRT, ONNX, quantization — making learned models fast and lean enough to run on constrained hardware at the edge.
View notes →Sensor Fusion & Perception
센서 융합 및 인식
Kalman filters, multi-modal sensing, depth cameras, and vision pipelines that let machines reliably perceive the real world.
View notes →Human-Robot Interaction
인간-로봇 상호작용
Designing safe, intuitive interfaces between people and robotic systems — from gesture recognition to natural language commands.
View notes →AI-Assisted Development
AI 지원 개발
Tools and methodologies for integrating AI into the software development process, enhancing productivity and code quality.
View notes →Physical AI Education
피지컬 AI 교육
Curriculum design, competency frameworks, and pedagogy for teaching Physical AI at the undergraduate and graduate level.
View notes →Safety and Ethics
안전 및 윤리
Research on safety and ethics in AI ensuring the safe and ethical deployment of AI systems.
View notes →Autonomous Robotics
자율 로봇공학
From gesture-controlled arms to ROS 2 systems that navigate and manipulate the physical world with increasing independence.
View notes →Embodied Intelligence
체화된 지능
AI that learns through physical interaction — perception-action loops, sensorimotor integration, and grounded cognition in robotic systems.
View notes →Digital Twin & Simulation
디지털 트윈 & 시뮬레이션
Sim-to-real transfer, virtual testbeds, and Isaac Sim pipelines — bridging the gap between simulation and deployment.
View notes →Industrial Applications
산업 응용
Applying Physical AI in manufacturing, logistics, and industrial automation for real-world impact.
View notes →Open Datasets
오픈 데이터셋
Curated datasets for Physical AI research, released openly to accelerate reproducible science.
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