Newton-type algorithms for robot motion optimization

The paper presents a class of Newton-type algorithms for the optimization of robot motions that take into account the dynamics. Using techniques from the theory of Lie groups and Lie algebras, the equations of motion of a rigid multibody system can be formulated in such a way that both the first and...

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Main Authors: Junggon Kim, Jonghyun Baek, Park, F.C.
Format: Conference Proceeding
Language:English
Subjects:
Aerodynamics
Aerospace engineering
Algebra
Convergence
Equations
Humans
Motor drives
Optimal control
Robot motion
Robustness
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creator Junggon Kim
Jonghyun Baek
Park, F.C.
description The paper presents a class of Newton-type algorithms for the optimization of robot motions that take into account the dynamics. Using techniques from the theory of Lie groups and Lie algebras, the equations of motion of a rigid multibody system can be formulated in such a way that both the first and second derivatives of the dynamic equations with respect to arbitrary joint variables can be computed analytically. The result is that one can formulate the exact gradient and Hessian of an objective function involving the dynamics, and develop efficient second-order Newton-type optimization algorithms for generating optimal robot motions. The methodology is illustrated with a nontrivial example.
doi_str_mv 10.1109/IROS.1999.811746
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Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289)</btitle><stitle>IROS</stitle><date>1999</date><risdate>1999</risdate><volume>3</volume><spage>1842</spage><epage>1847 vol.3</epage><pages>1842-1847 vol.3</pages><isbn>0780351843</isbn><isbn>9780780351844</isbn><abstract>The paper presents a class of Newton-type algorithms for the optimization of robot motions that take into account the dynamics. Using techniques from the theory of Lie groups and Lie algebras, the equations of motion of a rigid multibody system can be formulated in such a way that both the first and second derivatives of the dynamic equations with respect to arbitrary joint variables can be computed analytically. The result is that one can formulate the exact gradient and Hessian of an objective function involving the dynamics, and develop efficient second-order Newton-type optimization algorithms for generating optimal robot motions. 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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Aerodynamics
Aerospace engineering
Algebra
Convergence
Equations
Humans
Motor drives
Optimal control
Robot motion
Robustness
title Newton-type algorithms for robot motion optimization
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