This is the first year of a three-year continuing award. The research aims to develop a principled methodology with which to specify motions of an active observer, commonly referred to as the "next look" problem. The work will provide algorithms and techniques that can be used in mobile robot systems to control the robot's motion and to efficiently acquire sensory information about the robot's environment. The work consists of three primary areas of research. The first involves the development, and implementation in a real-time robotic system, of active vision algorithms for extraction of 3D environmental information. This includes structure from controlled camera motion, and structure from controlled illuminant motion. The second aspect of the work involves the development of a Bayesian data integration technique which will allow the 3D information acquired by multiple active vision modules over time to be integrated into a dynamic world or robot environment map. The third aspect is the development of a methodology for determining optimal and sub-optimal trajectories of active observers, based on the criteria of minimizing the time and computation required to reduce a global measure of uncertainty to below a set threshold.
