The Robotics Institute

My research focuses on developing computationally efficient algorithms to construct models of physical phenomena from massive amounts of noisy, ambiguous data. My approach is to pair theoretically sound, probabilistic, model-based reasoning with randomized approximation methods to attain efficiency.


I have exploited this theme in two major research projects prior to my thesis research: Texture-Based Tracking and
Monte Carlo Localization
(joint work with Dieter Fox). In my thesis research I exploit these same principles, but apply them to a problem of vastly greater complexity. In particular, I provide an efficient solution to the problem of building a 3D world model from 2D images, without correspondence.