The vision of Kris Kitani's lab is to realize robust autonomous systems built for real-world perception and interactive decision-making. The key focus areas of his lab are perception, decision-making, and interaction. His focus is broad because he believes that innovating at the system-level requires expertise and integration at the component level.
Kitani's lab innovates across the full spectrum of perception, including vision-based human pose estimation, action recognition, object detection/tracking/forecasting, and 3D scene understanding. They formulate models for decision-making, including approaches such as reinforcement learning, inverse reinforcement learning, imitation learning, and game-theoretic modeliing. They develop real-world systems to enable cyber-physical interaction, including wearable camera systems, multi-modal sensors, portable navigational aides, and assistive mobile robots.
