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Proceedings Paper

Knowledge-Based Route Planning Through Natural Terrain
Author(s): John F. Gilmore; Antonio C. Semeco; Pipat Eamsherangkoon
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Paper Abstract

The advent of advanced computer architectures for parallel and symbolic processing has evolved to the point where the technology currently exists for the development of prototype autonomous vehicles. Control of such devices will require communication between knowledge-based subsystems in charge of the vision, planning, and conflict resolution aspects necessary to make autonomous vehicles functional in a real world environment. This paper describes a heuristic route planning system capable of forming the planning foundation of a autonomous ground vehicle. The route planner described herein is applicable to a variety of natural terrain ground systems such as autonomous tactical vehicles and mobile robot sentries. The route planner discussed consists of four processing stages: (1) scene recognition, (2) route planning, (3) scene matching (4) knowledge-based validation. Each of these stages is discussed and examples are provided where appropriate.

Paper Details

Date Published: 5 April 1985
PDF: 10 pages
Proc. SPIE 0548, Applications of Artificial Intelligence II, (5 April 1985); doi: 10.1117/12.948415
Show Author Affiliations
John F. Gilmore, Georgia Tech Research Institute (United States)
Antonio C. Semeco, Georgia Tech Research Institute (United States)
Pipat Eamsherangkoon, Georgia Tech Research Institute (United States)

Published in SPIE Proceedings Vol. 0548:
Applications of Artificial Intelligence II
John F. Gilmore, Editor(s)

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