AFRL-Sponsored SuperBot Research Supports Air Force Information Dominance Published June 18, 2008 By Maria Callier, AFOSR/PIP Air Force Office of Scientific Research ARLINGTON, Va. -- AFRL is funding research aimed both at improving SuperBot prediction capabilities and at creating algorithms enabling the robot to detect surprise. SuperBot is a modular, multifunctional, and reconfigurable robot. Conceptually, it is a set of individual robots that work together to solve problems. Developing any technology that expands a robot's capacity to "learn" from its surroundings is a difficult undertaking, one demanding rigid investigation and meticulous mathematical calculation. The AFRL-sponsored effort to realize "surprise-based learning" is no exception. This research directly supports the Air Force vision of information dominance and "anywhere, anytime" operational readiness by facilitating the warfighter's ready assimilation of new information in a distributed fashion. Future robots will be capable of changing their own configurations in order to adapt in response to new and unexpected situations, such as those arising from space or ocean exploration efforts, disasters, or any similarly hazardous operational environment. These futuristic 'bots will possess self-healing properties as well, enhancing their resiliency to damage sustained during such missions. Leading the SuperBot research team is Dr. Wei-Min Shen, director of the University of Southern California (USC) Polymorphic Robotics Laboratory, associate director of the USC Center for Robotics and Embedded Systems, and research associate professor in USC's Computer Science Department. The National Aeronautics and Space Administration is interested in SuperBots and is incorporating the results of this AFRL program into a larger-scale SuperBot project that it is funding.