TY - GEN
T1 - USING A WAVELET NETWORK to CHARACTERIZE REAL ENVIRONMENTS for HAPTIC DISPLAY
AU - Miller, Brian E.
AU - Colgate, J. Edward
N1 - Publisher Copyright:
© 1998 American Society of Mechanical Engineers (ASME). All rights reserved.
PY - 1998
Y1 - 1998
N2 - This paper will introduce a framework for characterizing real environments, using recorded force/displacement data, for use in haptic display. Steps in the framework include data acquisition, identification, model verification, and implementation. Identification and implementation will be developed in detail. After obtaining a conceptual understanding of the roles data acquisition and model verification play in the process, the methods used in this paper will be described. To meet the requirement for the identification stage, a proven technique in nonlinear system identification will be adopted. This technique, called wavelet network, will provide a tool that is capable of identifying environments with significant nonlinear features. A theoretical development along with experimental results will be presented using a spring attached to a wall. This environment exhibits a linear region with a single nonlinearity. The wavelet network was chosen because it was designed specifically for use with problems of high input dimension. Therefore, it is the expectation that the procedure will be useful in identifying environments of varying complexity. Currently, the technique can be used to identify static nonlinear environments. Work is being done to extend its capabilities to handle dynamic environments.
AB - This paper will introduce a framework for characterizing real environments, using recorded force/displacement data, for use in haptic display. Steps in the framework include data acquisition, identification, model verification, and implementation. Identification and implementation will be developed in detail. After obtaining a conceptual understanding of the roles data acquisition and model verification play in the process, the methods used in this paper will be described. To meet the requirement for the identification stage, a proven technique in nonlinear system identification will be adopted. This technique, called wavelet network, will provide a tool that is capable of identifying environments with significant nonlinear features. A theoretical development along with experimental results will be presented using a spring attached to a wall. This environment exhibits a linear region with a single nonlinearity. The wavelet network was chosen because it was designed specifically for use with problems of high input dimension. Therefore, it is the expectation that the procedure will be useful in identifying environments of varying complexity. Currently, the technique can be used to identify static nonlinear environments. Work is being done to extend its capabilities to handle dynamic environments.
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U2 - 10.1115/IMECE1998-0263
DO - 10.1115/IMECE1998-0263
M3 - Conference contribution
AN - SCOPUS:84944113527
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
SP - 257
EP - 264
BT - Dynamic Systems and Control
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 1998 International Mechanical Engineering Congress and Exposition, IMECE 1998
Y2 - 15 November 1998 through 20 November 1998
ER -