A constraints-based method of the inverse kinematics for redundant manipulators

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 represented as an objective function to be optimized, other additional tasks can be represented as kinematic inequality constraints. In this paper, we reformulate a redundancy resolution problem with multiple criteria into a local constrained optimization problem, and propose a new method for solving it. The proposed method is especially efficient when the number of additional tasks is larger than the degree of redundancy. It also systematically assigns the priorities between the additional tasks. Besides of computational efficiency, the method has a cyclic property