Quadratically convergent algorithms for optimal dextrous hand grasping

Author

Helmke, Uwe ; Hüper, Knut ; Moore, John B.

Author_Institution

Dept. of Math., Wurzburg Univ., Germany

Volume

18

Issue

2

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

138

Lastpage

146

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

Keywords

Newton method; convergence of numerical methods; dexterous manipulators; gradient methods; linear programming; optimal control; Newton step size selection rule; Riemannian geometry; computational effort; gradient flow; grasp maps orthogonalization; iteration number; linearly constrained positive definite programming; optimal dextrous hand grasping; quadratically convergent algorithms; real-time dextrous-hand grasping; robotic balancing task; structural constraints; Computational geometry; Constraint optimization; Costs; Fingers; Friction; Grasping; Legged locomotion; Linear programming; Robot kinematics; Robot programming;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/TRA.2002.999643

Filename

999643