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Search Publications by: Craig I. Schlenoff (Fed)

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Displaying 176 - 200 of 300

Using ontologies to aid navigation planning in autonomous vehicles

December 31, 2004
Author(s)
Craig I. Schlenoff, Stephen B. Balakirsky, M Uschold, R Provine, S Smith
This paper explores the hypothesis that ontologies can be used to improve the capabilities and performance of on-board rout planning for autonomous vehicles. We name a variety of general benefits that ontologies may provide, and list numerous specific ways

Integrating Disparate Knowledge Representations Within 4D/RCS

November 1, 2004
Author(s)
James S. Albus, Craig I. Schlenoff, Rajmohan (. Madhavan, Stephen B. Balakirsky, Tony Barbera
In this paper, we show how the 4D/RCS architecture incorporates and integrates multiple types of disparate knowledge representation techniques into a common, unifying framework. 4D/RCS is based on the supposition that different knowledge representation

Ontology-Based Methods for Enhancing Autonomous Vehicle Path Planning

November 1, 2004
Author(s)
R Provine, Craig I. Schlenoff, Stephen B. Balakirsky, S Smith, M Uschold
We report the results of a first implementation demonstrating the use of an ontology to support reasoning about obstacles to improve the capabilities and performance of on-board route planning for autonomous vehicles. This is part of an overall effort to

Achieving intelligent performance in autonomous on-road driving

October 28, 2004
Author(s)
Craig I. Schlenoff, John Evans, Tony Barbera, James S. Albus, Elena R. Messina
This paper describes NIST?s efforts in evaluating what it will take to achieve autonomous human-level driving skills in terms of time and funding. NIST has approached this problem from several perspectives: considering the current stateof- the-art in

Task Analysis of Autonomous On-road Driving

October 28, 2004
Author(s)
Tony Barbera, John A. Horst, Craig I. Schlenoff, David Aha
The Real-time Control System (RCS) Methodology has evolved over a number of years as a technique to capture task knowledge and organize it into a framework conducive to implementation in computer control systems. The fundamental premise of this methodology