We study robust 3D mapping, geometry-aware learning, and adaptive navigation in dynamic settings.
We study video-language grounding and open-world recognition for long-term autonomous agents.
We study foundation models for robotic manipulation, task abstraction, and reusable control primitives.
We study uncertainty estimation, risk-sensitive inference, and robust deployment under distribution shift.
We study interactive 3D world models for simulation, prediction, and scalable embodied training pipelines.