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Proceedings Paper

Little Dog learning of tractive and compressive terrain characteristics
Author(s): Bruce L. Digney
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Paper Abstract

In recent years research into legged locomotion across extreme terrains has increased. Much of this work was done under the DARPA Learning Legged Locomotion program that utilized a standard Little Dog robot platform and prepared terrain test boards with known geometric data. While path planing using geometric information is necessary, acquiring and utilizing tractive and compressive terrain characteristics is equally important. This paper describes methods and results for learning tractive and compressive terrain characteristics with the Little Dog robot. The estimation of terrain traction and compressive/support capabilities using the mechanisms and movements of the robot rather than dedicated instruments is the goal of this research. The resulting characteristics may differ from those of standard tests, however they will be directly usable to the locomotion controllers given that they are obtained in the physical context of the actual robot and its actual movements. This paper elaborates on the methods used and presents results. Future work will develop better suited probabilistic models and interwave these methods with other purposeful actions of the robot to lessen the need for direct terrain probing actions.

Paper Details

Date Published: 23 May 2011
PDF: 19 pages
Proc. SPIE 8045, Unmanned Systems Technology XIII, 80450I (23 May 2011); doi: 10.1117/12.883276
Show Author Affiliations
Bruce L. Digney, Defence Research and Development Canada (Canada)

Published in SPIE Proceedings Vol. 8045:
Unmanned Systems Technology XIII
Douglas W. Gage; Charles M. Shoemaker; Robert E. Karlsen; Grant R. Gerhart, Editor(s)

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