Quadratically convergent algorithms for optimal dextrous hand grasping

Uwe Helmke; Knut Hüper; John B. Moore

doi:10.1109/TRA.2002.999643

Quadratically convergent algorithms for optimal dextrous hand grasping

Uwe Helmke^*, Knut Hüper, John B. Moore

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

69 Citations (Scopus)

Abstract

There is a robotic balancing task, namely real-time dextrous-hand grasping, for which linearly constrained, positive definite programming gives a quite satisfactory solution from an engineering point of view. We here propose refinements of this approach to reduce the computational effort. The refinements include elimination of structural constraints in the positive definite matrices, orthogonalization of the grasp maps, and giving a precise Newton step size selection rule.

Original language	English
Pages (from-to)	138-146
Number of pages	9
Journal	IEEE Transactions on Robotics and Automation
Volume	18
Issue number	2
DOIs	https://doi.org/10.1109/TRA.2002.999643
Publication status	Published - Apr 2002

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10.1109/TRA.2002.999643

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KW - Dextrous hand

KW - Gradient flow

KW - Newton algorithm

KW - Optimal grasping

KW - Positive definite programming

KW - Riemannian geometry

KW - Robotic hand

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Quadratically convergent algorithms for optimal dextrous hand grasping

Abstract

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