This award funds the first year of a five-year Presidential Young Investigator Award for research into an understanding of the information requirements of manipulation tasks. The aim is to develop a high-level representation of tasks that facilitates the decomposition into subtasks and the translation of high-level specifications into low-level robot commands. Such translation is complicated by uncertainties which may propagate through the system. A manipulation language will be developed to support task decomposition and abstraction, and several types of manipulation tasks will be studied, including parts orienting, assembly by implosion, and large-scale mounting operations. The project will study information flow among the decomposed subtasks. This research should lead to a better understanding of the fundamentals of manipulation, a better characterization of the relations among information, speed of assemble, and task solvability, and a better understanding of how to design robots for operation in a world with uncertainties.//
