Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distan...

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Bibliographic Details
Main Authors: Jaehyun Shin, Yongmin Zhong, Denny Oetomo, Chengfan Gu
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Sensors
Subjects:
soft tissue characterization
Hunt-Crossley model
unscented Kalman filter
contact model error
strong tracking
and random weighting
Online Access:http://www.mdpi.com/1424-8220/18/5/1650

Internet

http://www.mdpi.com/1424-8220/18/5/1650

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