Learning Rough Terrain Outdoor Navigation

December 12, 2009

UPI rough terrain navigation system.

Online modeling of experience base for potential environmental hazards

Learning Rough-Terrain Autonomous Navigation, by J. A. Bagnell, D. M. Bradley, D. Silver, B. Sofman, A. Stentz. Currently under review for Robotics and Automation Magazine.

Autonomous navigation by a mobile robot through natural, unstructured terrain is one of the premier challenges in field robotics. The DARPA UPI program was tasked with advancing the state of the art in robust autonomous performance through challenging and widely varying environments. In order to accomplish this goal, machine learning techniques were heavily utilized to provide robust and adaptive performance, while simultaneously reducing the required development and deployment time. This paper describes the autonomous system, Crusher, developed for the UPI program, and the learning approaches that aided in its successful performance.

A short video of the UPI system’s performance leveraging the learning techniques discussed can be seen by clicking on the image to the left.

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