Nonlinear Kalman Filtering for Force-Controlled Robot Tasks - Lefebvre, Tine;Bruyninckx, Herman;de Schutter, Joris
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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…mehr

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Produktbeschreibung
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.
Rezensionen
From the reviews: "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)