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Springer Tracts in Advanced Robotics

By: Tine Lefebvre, Herman Bruyninckx, Joris de Schutter

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Hardcover | 20 September 2005

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Hardcover
286 Pages

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23.5 x 15.88 x 1.91

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This monograph focuses on how to achieve more robot autonomy by means of reliable processing skills. "Nonlinear Kalman Filtering for Force-Controlled Robot Tasks " discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan optimization for improved estimation accuracy. Kalman filtering techniques are applied to identify the contact state based on force sensing between a grasped object and the environment. The potential of this work is to be found not only for industrial robot operation in space, sub-sea or nuclear scenarios, but also for service robots operating in unstructured environments co-habited by humans where autonomous compliant tasks require active sensing.

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"The present book provides the latest developments in the area of contact modeling, nonlinear parameter estimation and parameter estimation and parameter estimation improvement accuracy of robots. ... The book includes an up-to-date bibliography and a lot of numerical examples. The Appendices provide various theoretical complements which are of high interest for researchers working in robotics. The graphics is excellent and the final list of symbols and abbreviations are very useful. The book is an excellent contribution in the area of robotics ... ." (Dumitru Stanomir, Zentralblatt MATH, Vol. 1120 (22), 2007)

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Engineering & Technology Electronics & Communications Engineering Electronics Engineering Automatic Control Engineering Robotics Mathematics Applied Mathematics Reference, Information & Interdisciplinary Subjects

Research & Information Information theory Cybernetics & Systems Theory Energy Technology & Engineering Electrical Engineering

Introduction	p. 1
Literature survey : autonomous compliant motion	p. 11
Literature survey : Bayesian probability theory	p. 25
Kalman filters for nonlinear systems	p. 51
The non-minimal state Kalman filter	p. 77
Contact modelling	p. 95
Geometrical parameter estimation and CF recognition	p. 121
Experiment : a cube-in-corner assembly	p. 139
Task planning with active sensing	p. 165
General conclusions	p. 199
The linear regression Kalman filter	p. 205
The non-minimal state Kalman filter	p. 211
Frame transformations	p. 219
Kalman filtering for non-minimal measurement models	p. 223
Partial observation with the Kalman filter	p. 227
A NMSKF linearizing state for the geometrical parameter estimation	p. 231
CF-observable parameter space for twist and pose measurements	p. 235
Table of Contents provided by Blackwell. All Rights Reserved.

Springer Tracts in Advanced Robotics

At a Glance

Hardcover

Industry Reviews

Shipping

How to return your order

Defective items

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