Michael Kaess

I am interested in mobile robot autonomy. One of the first problems encountered when robots operate outside controlled factory and research environments is the need to perceive their surroundings. My research focuses on efficient inference at the connection of linear algebra and probabilistic graphical models for 3D mapping and localization.

I have previously been a Research Scientist and a Postdoctoral Associate at the Massachusetts Institute of Technology (MIT), in John Leonard's Marine Robotics Lab. In 2008 I have received my PhD in Computer Science from the Georgia Institute of Technology, advised by Frank Dellaert.

Perception is a fundamental challenge for mobile robots navigating through and interacting with their environment. My research focuses on 3D mapping and localization using information from any available sensor, including vision, laser, inertial, GPS and sonar (underwater). To enable online operation, my research also explores novel algorithms for efficient and robust inference at the intersection of linear algebra and probabilistic graphical models