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There are a total of 86 record(s) matching your query.
Sorted by: Date Added To NTRS in Descending order
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Iterative Repair Planning for Spacecraft Operations Using the Aspen System
Author(s): Rabideau, G.; Knight, R.; Chien, S.; Fukunaga, A.; Govindjee, A.
Abstract: This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations ...
NASA Center: Jet Propulsion Laboratory Publication Year: 2000
Added to NTRS: 2008-06-02
Document ID: 20000052465
Sequence-of-events-driven automation of the deep space network
Author(s): Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.
Abstract: In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the ...
NASA Center: Jet Propulsion Laboratory Publication Year: 1996
Added to NTRS: 2008-06-02
Accession Number: 96N25261; Document ID: 19960022228
Using Artificial Intelligence Planning to Automate Science Image Data Analysis
Author(s): Fisher, F.; Chien, S.; Lo, E.; Mortensen, H.; Greeley, R.
Abstract: In recent times, improvements in imaging technology have made available an incredible array of information in image format.
NASA Center: Jet Propulsion Laboratory Publication Year: 1999
Added to NTRS: 2006-12-25
Document ID: 20060040605
Integrating Model-based Artificial Intelligence Planning with Procedural Elaboration for Onboard Spacecraft Autonomy
Author(s): Knight, R.; Chien, S.; Knight, R.; Gat, E.; Starbird, T.; Gostelow, K.; Keller, B.; Smith, W.
Abstract: This paper describes the integration of a model-based planner into a procedural architecture.
NASA Center: Jet Propulsion Laboratory Publication Year: 2000
Added to NTRS: 2006-12-25
Document ID: 20060032755
An Automated Rover Command Generation Prototype for the Mars 2003 Marie Curie Rover
Author(s): Sherwood, R.; Estlin, T.; Chien, S.; Rabideau, G.; Engelhardt, B.; Mishkin, A.
Abstract: This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities.
NASA Center: Jet Propulsion Laboratory Publication Year: 2000
Added to NTRS: 2006-12-25
Document ID: 20060032782
Using Artificial Intelligence Planning to Automate SAR Image Processing for Scientific Data Analysis
Author(s): Fisher, F.; Chien, S.; Lo, E.; Greeley, R.
Abstract: In recent times, improvements in imaging technology have made available an incredible array of information in image format.
NASA Center: Jet Propulsion Laboratory Publication Year: 1998
Added to NTRS: 2006-12-25
Document ID: 20060041650
Goal-driven Automation of a Deep Space Communications Station: A Case Study in Knowledge Engineering for Plan Generation and Execution
Author(s): Hill, R. W., Jr.; Chien, S. A.; Fayyad, K. V.; Chien, S.
Abstract: This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a Communication ...
NASA Center: Jet Propulsion Laboratory Publication Year: 1997
Added to NTRS: 2006-12-25
Document ID: 20060041725
Feature extraction and classification for EO-1 hyperspectral imagery
Author(s): Castano, B.; Chien, S.; Cichy, B.; Prentice, S.; Tang, N.
Abstract: No Abstract Available
NASA Center: Jet Propulsion Laboratory Publication Year: 2003
Added to NTRS: 2006-12-25
Document ID: 20060029317
Replanning Using Hierarchical Task Network and Operator-Based Planning
Author(s): Wang, X.; Chien, S.
Abstract: In order to scale-up to real-world problems, planning systems must be able to replan in order to deal with changes in problem context. In this paper we describe hierarchical task network and operatorbased re-planning ...
NASA Center: Jet Propulsion Laboratory Publication Year: 1997
Added to NTRS: 2006-12-25
Document ID: 20060035483
A Statistical Approach to Adaptive Problem-Solving for Large-Scale Scheduling and Resource Allocation Problems
Author(s): Chien, S.; Gratch, J.; Burl, M.
Abstract: Our work focuses upon development of techniques for choosing among a set of alternatives in the presence of incomplete information and varying costs of acquiring information.
NASA Center: Jet Propulsion Laboratory Publication Year: 1994
Added to NTRS: 2006-12-25
Document ID: 20060037801
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