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Convergence properties of gradient-based numerical motion-optimizations for manipulator arms amid static or moving obstacles

Published online by Cambridge University Press:  15 November 2004

Jong-keun Park
Jong-keun Park
Affiliation:
Dept. Mechanical and Automation Engr., Kyungnam University, Masan 631-701 (South Korea) E-mail: jkpark@kyungnam.ac.kr
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Abstract

This paper demonstrates the convergence stability and the actual usefulness of the gradient-based motion optimizations for manipulator arms. An optimal motion-planning problem is converted into a finite-dimensional nonlinear programming problem that utilizes cubic or quintic B-splines as basis functions. This study shows that the numerically calculated gradient is a useful tool in finding minimum torque, minimum energy, minimum overload, and minimum time motions for manipulator arms in the presence of static or moving obstacles. A spatial 6-link manipulator is simulated without simplifying any of the kinematic, dynamic or geometric properties of the manipulator or obstacles.

Keywords

Optimal motionRobot manipulatorNonlinear programmingQuasi-Newton methodPenetration growth distance
Type
Research Article
Information
Robotica , Volume 22 , Issue 6 , November 2004 , pp. 649 - 659
Copyright
© 2004 Cambridge University Press

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