Lab Meeting September 8th, 2008 (fish60): High Performance Outdoor Navigation from Overhead Data using Imitation Learning

David Silver, J. Andrew Bagnell, Anthony StentzRobotics Institute, Carnegie Mellon UniversityPittsburgh, Pennsylvania USA
Robotics Science and Systems, June, 2008

High performance, long-distance autonomous navigationis a central problem for field robotics. Recently, a class of machine learning techniques have been developed that rely upon expert human demonstration to develop a function mapping overhead data to traversal cost. In this work, we extend these methods to automate interpretation of overhead data. We address key challenges, including interpolation-based planners, non-linear approximation techniques, and imperfect expert demonstration, necessary to apply these methods for learning to search for effective terrain interpretations.

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