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Search Publications by: Craig I. Schlenoff (Fed)

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Displaying 76 - 100 of 150

Test Methods and Knowledge Representation for Urban Search and Rescue Robots

August 17, 2007
Author(s)
Craig I. Schlenoff, Elena R. Messina, Alan M. Lytle, Brian A. Weiss, Ann M. Virts
In this paper, we described an effort in which NIST is working with FEMA Task Force members to define performance requirements and standard test methods as well as to assess the deployment potential of robots applied to the USAR domain. This process has

Performance Analysis of Symbolic Road Recognition for On-Road Driving

January 31, 2007
Author(s)
Mike Foedisch, Craig I. Schlenoff, Rajmohan Madhavan
Previous approaches to road sensing, namely road detection were based on segmenting the sensor data, i.e. color camera image, into road and non-road areas. Performance evaluation for such algorithms could be performed in a relatively straightforward

Technology Evaluations and Performance Metrics for Soldier-Worn Sensors for ASSIST

January 31, 2007
Author(s)
Brian Weiss, Craig I. Schlenoff, Michael O. Shneier, Ann Virts
The DARPA-funded Advanced Soldier Sensor Information Systems and Technology (ASSIST) project is aimed at developing soldier-worn sensors to increase a soldier s battlefield awareness during humanitarian and combat missions, provide them with data

A Standard Intelligent System Ontology

June 27, 2006
Author(s)
Craig I. Schlenoff, R Washington, Anthony J. Barbera, C Manteuffel
The level of automation in combat vehicles being developed for the Army?s objective force is greatly increased over the Army?s legacy force. This automation is taking many forms in emerging vehicles; varying from operator decision aides to fully autonomous

An Intelligent Ground Vehicle Ontology for Multi-Agent System Integration

June 27, 2006
Author(s)
Craig I. Schlenoff, R Washington, Anthony J. Barbera
The level of automation in ground combat vehicles being developed for the Army?s objective force is greatly increased over the Army?s legacy force. The development of these intelligent ground vehicles (IGV) requires a thorough understanding of all of the

A Robot Ontology for Urban Search and Rescue

June 26, 2006
Author(s)
Craig I. Schlenoff, Elena R. Messina
The goal of this Robot Ontology effort is to develop and begin to populate a neutral knowledge representation (the data structures) capturing relevant information about robots and their capabilities to assist in the development, testing, and certification

Towards an Approach for Knowledge-Based Road Detection

June 26, 2006
Author(s)
Mike Foedisch, Craig I. Schlenoff, Michael O. Shneier
Our previous work on road detection suggests the usage of prior knowledge in order to improve performance. In this paper we will explain our motivation for a novel approach, define requirements and point out issues, particularly concerning the

Using 4D/RCS to Address AI Knowledge Integration

June 26, 2006
Author(s)
Craig I. Schlenoff, James S. Albus, Elena R. Messina, Tony Barbera, Rajmohan (. Madhavan, Stephen B. Balakirsky
In this paper, we show how 4D/RCS incorporates and integrates multiple types of disparate knowledge representation techniques into a common, unifying architecture. 4D/RCS is based on the supposition that different knowledge representation techniques offer

Overview of the First Advanced Technology Evaluations for ASSIST

January 31, 2006
Author(s)
Craig I. Schlenoff, Brian A. Weiss, Michelle P. Steves, Ann M. Virts, Michael O. Shneier, Michael Linegang
ASSIST (Advanced Soldier Sensor Information Systems Technology) is a DARPA-funded effort whose goal is to exploit soldier-worn sensors to augment the soldier s recall and reporting capability to enhance situation understanding. ASSIST is separated into two

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