Of course, a central problem area is the development of methods for interpreting and using sensor information. However, these methods must match the capabilities of the system. Consequently research also focuses on optimizing the use of sensing equipment and computer resources to gather and process information for a particular task. In changing worlds, the plan must contain rules for reacting to problems, but in addition there must be a planning module with a more long-range outlook that can revise the plan before execution is completed. Understanding this ability requires a deep understanding of the techniques in simplifying mathematical models, finding approximate solutions, and deriving consequences from mathematical models by mixed symbolic, numerical, and geometric computations.
Current research involves the automatic analysis of certain classes of fluid dynamics problem.
Our goal is to produce computer programs that not only serve as high-level assistants to scientists and engineers but also smart enough to carry out independent research in fluid dynamics and write research papers of publishable quality. One of the fundamental goals of computer vision is to recognize the three-dimensional objects in a single perspective projection image in terms of a database of object models. At Yale, we have focussed on recognition of curved objects where it is more difficult establish such a correspondence. Faculty members working in Artificial Intelligence are Gregory Hager, David Kriegman, Drew McDermott, Francois Meyer, Willard Miranker, Marcello Pelillo, and Steven Zucker. Michael Hines, and Kaleem Siddiqi are Research Scientists.