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Proceedings Paper

Model-Based Reasoning Of Sensory Data For Robotic Assembly
Author(s): E. S. H. Hou
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Paper Abstract

Sensory data provide crucial information for controlling and monitoring the execution of an assembly operation. Moreover, in the event that an error occurs during the assembly operation, this information is needed to determine the state of the assembly operation, the type of error, and the appropriate error-recovery procedure to correct the error. This paper addresses the problem of monitoring and interpreting sensory data acquired during robotic assembly. Sensory data are classified as spatial, physical, and temporal, and abstract model for each type of sensory data are developed. Each sensor provides information about the state of the assembly operation and through the use of evidential reasoning, this information is combined to obtain a combined state of the assembly operation. With this combined state of the assembly operation, we can monitor the progress of the assembly operation. In the event of an error in the assembly operation, error-recovery procedure based on low-level motions of the manipulator are selected depending on the sensory information.

Paper Details

Date Published:
PDF: 5 pages
Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, ; doi: 10.1117/12.970003
Show Author Affiliations
E. S. H. Hou, New Jersey Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1198:
Sensor Fusion II: Human and Machine Strategies
Paul S. Schenker, Editor(s)

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