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You searched on: Author: craig schlenoff

Displaying records 31 to 40 of 109 records.
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31. Performance Evaluation of Speech Translation Systems
Published: 5/28/2008
Authors: Brian A Weiss, Craig I Schlenoff, Gregory A Sanders, Michelle Potts Steves, Sherri Condon, Jon Phillips, Dan Parvaz
Abstract: One of the most challenging tasks for uniformed service personnel serving in foreign countries is effective verbal communication with the local population. To remedy this problem, several companies and academic institutions have been funded to develo ...

32. Performance Evaluation of Cost-Based vs. Fuzzy-Logic-Based Prediction Approaches in PRIDE
Published: 3/20/2008
Authors: Zeid Kootbally, Craig I Schlenoff, Rajmohan Madhavan, Sebti Foufou
Abstract: PRIDE (PRediction In Dynamic Environments) is a hierarchical multi-resolutional framework for moving object prediction. PRIDE incorporates multiple prediction algorithms into a single, unifying framework. To date, we have applied this framework to pr ...

33. Concepts of Operations for Robot-Assisted Emergency Response and Implications for Human-robot Interaction
Published: 1/7/2008
Authors: Jean Scholtz, Brian Antonishek, Brian C Stanton, Craig I Schlenoff
Abstract: In this paper we discuss a field study at Disaster City?, Texas in March 2006. First Responders and robot developers tried out various concepts of operations in a number of disaster scenarios. Observations, video data, and questionnaire data were ana ...

34. A Brief History of PRIDE
Published: 12/28/2007
Authors: Zeid Kootbally, Craig I Schlenoff, Rajmohan Madhavan
Abstract: PRIDE (PRediction In Dynamic Environments) is a framework that provides an autonomous vehicle's planning system with information that it needs to perform path planning in the presence of moving objects. The underlying concept is based upon a mult ...

35. Driver Aggressivity Analysis Within the Prediction In Dynamic Environments (PRIDE) Framework
Published: 10/19/2007
Authors: Craig I Schlenoff, Zeid Kootbally, Rajmohan Madhavan
Abstract: PRIDE is a hierarchical multiresolutional framework for moving object prediction that incorporates multiple prediction algorithms into a single, unifying framework. PRIDE is based upon the 4D/RCS (Real-time Control System) reference model architectur ...

36. Test Methods and Knowledge Representation for Urban Search and Rescue Robots
Published: 8/17/2007
Authors: Craig I Schlenoff, Elena R Messina, Alan M. (Alan M.) Lytle, Brian A Weiss, Ann M Virts
Abstract: 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 ...

37. Performance Analysis of Symbolic Road Recognition for On-Road Driving
Published: 1/31/2007
Authors: Mike Foedisch, Craig I Schlenoff, Rajmohan Madhavan
Abstract: 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 ...

38. Technology Evaluations and Performance Metrics for Soldier-Worn Sensors for ASSIST
Published: 1/31/2007
Authors: Brian A Weiss, Craig I Schlenoff, Michael O Shneier, Ann M Virts
Abstract: 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 col ...

39. The Effect of Process Models on Short-term Prediction of Moving Objects for Autonomous Driving
Published: 6/28/2006
Authors: Rajmohan Madhavan, Craig I Schlenoff
Abstract: We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorpor ...

40. A Standard Intelligent System Ontology
Published: 6/27/2006
Authors: Craig I Schlenoff, R Washington, Anthony J Barbera, C Manteuffel
Abstract: 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 auto ...

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