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Proceedings Paper

An Intelligent Training System For Payload-Assist Module Deploys
Author(s): R. Bowen Loftin; Lui Wang; Paul Baffes; Monica Rua
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Paper Abstract

An autonomous intelligent training system has been produced for use by Mission Control Center (MCC) Flight Dynamics Officers (FDOs) training to perform payload-assist module (PAM) deploys from the orbiter. The system (designated PD/ICAT for PAM Deploy Intelligent computer-Aided Training) integrates expert system technology with teaching/training methodologies. Five basic components comprise the system. A domain expert (DeplEx for Deploy Expert) contains the rules and procedural knowledge needed by the FDOs in carrying out a PAM deploy. DeplEx also contains "mat-rules" which encode the errors commonly made by novice FDOs. A trainee model is developed for each individual using the system. The model uniquely represents each trainee's current skill level and history o f interactions with the system. The training system manager (TSM) examines the actions of the trainee and compares them with the actions of DeplEx within the same operational environment. The actions (correct, optional, or incorrect) are noted and the probable cause of incorrect actions is diagnosed using Deplex's mal-rules. A unique feature of the TSM is its ability to permit the trainee the freedom to follow any valid path between two steps of the deploy process. Following each trainee action, evaluative assertions are made by the ITS and used to update the trainee model. A training scenario generator designs appropriate training exercises for each trainee based on his model and the training goal(s) established by the TSM. A user interface has been designed which permits the trainee to access data and take actions in much the same manner as he would at his console in the MCC.

Paper Details

Date Published: 31 October 1987
PDF: 9 pages
Proc. SPIE 0851, Space Station Automation III, (31 October 1987); doi: 10.1117/12.942918
Show Author Affiliations
R. Bowen Loftin, University of Houston (United States)
Lui Wang, NASA/Johnson Space Center (United States)
Paul Baffes, NASA/Johnson Space Center (United States)
Monica Rua, NASA/Johnson Space Center (United States)


Published in SPIE Proceedings Vol. 0851:
Space Station Automation III
Wun C. Chiou, Editor(s)

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