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JFR
2006

Learning from examples in unstructured, outdoor environments

13 years 3 months ago
Learning from examples in unstructured, outdoor environments
In this paper, we present a multi-pronged approach to the "Learning from Example" problem. In particular, we present a framework for integrating learning into a standard, hybrid navigation strategy, composed of both plan-based and reactive controllers. Based on the classification of colors and textures as either good or bad, a global map is populated with estimates of preferability in conjunction with the standard obstacle information. Moreover, individual feedback mappings from learned features to learned control actions are introduced as additional behaviors in the behavioral suite. A number of real-world experiments are discussed that illustrate the viability of the proposed method.
Jie Sun, Tejas R. Mehta, David Wooden, Matthew Pow
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where JFR
Authors Jie Sun, Tejas R. Mehta, David Wooden, Matthew Powers, James M. Rehg, Tucker R. Balch, Magnus Egerstedt
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