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Abstraction has long been recognized as a tool for making planning problems more tractable through mechanisms such as plan refinement. In this talk, we will turn our attention to a less popular role that abstraction can play: as an enabler of interleaved planning and execution.
I will present a formal framework which includes a set of abstract problem spaces in the overall robot architecture. Using this framework, we can explore ways in which abstraction can add rationality to a robot architecture without endangering the robot's real-time guarantees.
Illah Nourbakhsh is Assistant Professor of Robotics at Carnegie Mellon. His research spans the formal properties, design and implementation of Robot Architectures and communication and cooperation between groups of autonomous systems. In the fall, Illah will be teaching a new undergraduate and graduate robotics class, featuring hands-on robot programming for two mobile robot bases. He received his Ph.D. in Computer Science from Stanford University in 1996 and was a member of the NewMAAP Rapid Prototyping Team at Nasa/JPL.
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