Perception R&D for Unmanned Systems at iRobot
Dr. Christopher Geyer
Senior Principal Research Scientist
Tuesday, January 15th, 2013
Abstract: The ability to effectively perceive the world is key to virtually all robots. Perception enables autonomy, and can be used to make interaction between robot and people more natural. For some time, however, a lack of effective and embeddable perception algorithms has been an obstacle to autonomous, people-friendly robots. Recently, though, there has been a convergence of both increased computational performance and more reliable algorithms that are enabling “smarter” robotic behaviors and more natural modes of interaction. In this presentation, I will talk research at iRobot in computer vision and perception, and their applications to problems in unmanned systems. I will discuss joint work with UC Berkeley and Brown University to develop a real-time object recognition capability, as well as work in activity recognition with Colorado State University.
Dr. Geyer is a Senior Principal Research Scientist at iRobot Corporation. He joined iRobot in 2008, coming from Carnegie Mellon University’s Robotics Institute, where he participated in the DARPA Urban Challenge and conducted research in perception for unmanned systems. Dr. Geyer started his career in robotics in the GRASP Lab at the University of Pennsylvania, where he received his B.S.E. and Ph.D. in Computer Science in 1999 and 2002, respectively, and was a post-doc at U.C. Berkeley, where he lead the development of an autonomous landing capability for an unmanned helicopter.
January 15, 2013