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CS Seminar, Monday, March 1, 3-4 PM, EE Packard Bldg., rm. 202 (Stanford Main Campus)

A Framework to Synergistically Combine Motion Planning in Continuous Spaces
and High-Level Planning in Discrete Spaces

Abstract:

Research in robotics has focused since its inception towards increasing the
ability of robots to plan and act on their own in order to safely complete
high-level tasks.

Toward this goal, this talk presents a multi-layered framework that
efficiently plans the sequence of motions the robot needs to execute so that
the resulting trajectory is dynamically feasible, avoids collisions, and
satisfies a given high-level specification. In distinction from traditional
motion planning, the framework can take into account high-level
specifications given by Finite State Machines, Hybrid Automata, Linear
Temporal Logic, STRIPS, and other planning-domain definition languages. Such
expressive models make it possible to specify complex tasks that frequently
arise in mobile robotics, manipulation, robotic-assisted surgery,
search-and-rescue missions, and air-traffic management.

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