The eye sees only what the mind is prepared to comprehend.
—Henri Bergson, French philosopher
In the Robotics Institute at Newel Simon Hall, Carnegie Mellon graduate student Dan Munoz is working to develop this connection between "seeing" and "understanding," though not in a philosophical sense.
His work is with artificial intelligence, focusing on machine learning and computer vision. He designs algorithms that give machines the ability to identify unknown objects in their environments. One method is to shoot laser beams onto an object to get a three-dimensional "picture" and then feed the rate of return into a series of algorithms to identify the object.
"I think it's pretty interesting that we have all these fancy computers that can beat the best people in chess, that can do a lot of number-crunching for protein analysis, but then we have something as simple as an insect that can navigate through this world without walking over a cliff," says Munoz. "Comparatively, computers are not even close to being as sophisticated as nature."
In closing that gap, his research can be applied to both the public and private sectors, whether helping utility companies use autonomous machines for their field work or developing intelligent GPS systems for self-driving military vehicles. Having already earned a master's degree in robotics from Carnegie Mellon in 2007, Munoz's research with the U.S. Army Research Laboratory has led him to receive the first QinetiQ North America Robotics Fellowship. He is the first recipient, and the fellowship will carry him three years into his PhD and also provide him with an internship with QinetiQ North America, a technology and product-development group.
—Danielle Commisso (HS'06)
