Research
Our scientific interests are driven by the desire to build intelligent robots, computers and embedded systems, which are capable of servicing people more efficiently than equivalent manned systems in a wide variety of dynamic and unstructured environments. We are primarily driven by the problems of how robots learn about their environment under uncertainty and with incomplete information. As computers and sensors become ubiquitous, the importance and need of scene understanding will increase substantially in the coming decades. Theoretical frameworks as well as computationally efficient algorithms have to be established and developed at the intersection of machine perception, machine learning, control, statistics and optimization. We believe that finding a solution to scene understanding is a key prerequisite for making robotic systems truly autonomous and making many potential applications feasible.
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Last Updated: Feb. 13, 2011.