A constrained optimization approach to resolving manipulator redundancy

Abstract

A redundant manipulator can achieve additional tasks by utilizing the degree of redundancy, in addition to a basic motion task. While some additional tasks can be performed by optimizing a proper objective function, other additional tasks can be performed by satisfying a set of kinematic inequality constraints. In this article, we reformulate a redundancy resolution problem with multiple criteria into a local equality and inequality constrained optimization problem, and propose a method to solve it at velocity level. The proposed method is efficient, especially when the number of additional tasks is larger than the degree of redundancy. It also systematically assigns the priorities between the additional tasks. Besides the computational efficiency, the method has a cyclic property. © 1996 John Wiley & Sons, Inc.