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Least squares methods and applications in robotics
Linköping University, Department of Mathematics. Linköping University, The Institute of Technology.
1994 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis consider the least squares problems and various applications to the inverse kinematic problem in robotics. Two main linear least squares results are given; new backward perturbation bounds and an adaptive algorithm for rank-I regularization for rank deficient linear least squares problems. The inverse kinematic problem, i.e. the problem of finding the joint angles of a robot so that a given position and orientation condition is satisfied, is here formulated as a set of nonlinear equations. A general solver using Gauss-Newton's method is implemented on a fast signal processor. Methods to handle kinematic singularities are discussed, and the regularization algorithm proposed is used. Finally we consider redundant robots, where the number of joints is 7 or more. The extra degrees of freedom are here used for obstacle avoidance, a practical implementation strategy is proposed where the obstacles are assumed to be convex.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet , 1994. , p. 124
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 332
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-143503ISBN: 9178712076 (print)OAI: oai:DiVA.org:liu-143503DiVA, id: diva2:1164375
Public defence
1994-01-31, Elysion, Tema-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Available from: 2017-12-11 Created: 2017-12-11 Last updated: 2018-01-09Bibliographically approved

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  • apa
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  • Other locale
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Output format
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