Research Interest
Research Interest
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We aim to develop a Robust Physical AI system that can perceive, understand,
and navigate a dynamic world, even in challenging environments!
We aim to develop a Robust Physical AI system that can perceive, understand,
and navigate a dynamic world, even in challenging environments!
These are the research topics that we are interested in (but not limited to):
These are the research topics that we are interested in (but not limited to):
Robust Robot Learning
Deep Reinforcement Learning for Robot/Sensor Control (Humanoid, Legged Robot, Manipulator, Vision/Tactile/Audio/Olfactory/Taste Sensor, etc)
Multi-modal Sensor Fusion for Robust Spatial/Semantic Perception
Vision-Language Navigation/Manipulation
Scalable Representation Learning
Learning from Self-supervision (Image, Video, Action, Audio, Language, etc)
Learning from Multi-Sensor Data (RGB, NIR, SWIR, Thermal, Event camera, (Spinning, Solid-state) LiDAR, RADAR, Sonar, etc)
Foundation Model for Multi-modal Sensors/Robotics (VLM, LBM, etc)
Robust Spatial/Semantic Understanding in-the-wild
Robust Robot Perception in Adverse Conditions (Rainy, Snowy, Dusty, Over-exposed, Fired, Low-lighted, etc)
Vision-Language Understanding in Adverse Conditions
Self-supervised 3D Geometry (Depth, Optical Flow, Scene flow, Odometry, Object pose, SLAM)
Continual Learning/Domain Adaptation in the wild
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