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Proceedings Paper

Symbolic perception-based autonomous driving in dynamic environments using 4D/RCS
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Paper Abstract

4D/RCS is a hierarchical architecture designed for the control of intelligent systems. One of the main areas that 4D/RCS has been applied to recently is the control of autonomous vehicles. To accomplish this, a hierarchical decomposition of on-road driving activities has been performed which has resulted in implementation of 4D/RCS tailored towards this application. This implementation has seven layers and ranges from a journey manager which determines the order of the places you wish to drive to, through a destination manager which provides turn-by-turn directions on how to get to a destination, through a route segment, drive behavior, elemental maneuver, goal path trajectory, and then finally to servo controllers. In this paper, we show, within the 4D/RCS architecture, how knowledge-driven top-down symbolic representations combined with low-level bottom-up tasks can synergistically provide valuable information for on-road driving better than what is possible with either of them alone. We demonstrate these ideas using field data obtained from an Unmanned Ground Vehicle (UGV) traversing urban on-road environments.

Paper Details

Date Published: 2 May 2007
PDF: 12 pages
Proc. SPIE 6561, Unmanned Systems Technology IX, 65611T (2 May 2007); doi: 10.1117/12.720225
Show Author Affiliations
M, Foedisch, National Institute of Standards and Technology (United States)
R. Madhavan, National Institute of Standards and Technology (United States)
C. Schlenoff, National Institute of Standards and Technology (United States)

Published in SPIE Proceedings Vol. 6561:
Unmanned Systems Technology IX
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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