Predictive online inverse kinematics for redundant manipulators

Abstract

Determining the optimal solution for the inverse kinematics of redundant robots has been the focus of much previous research. Instantaneous approaches are computationally efficient, but may cause high joint velocities due to their local character. In this paper, we present an efficient implementation of a global approach following Pontryagin's Minimum Principle for online calculation. Within a moving horizon, we exploit the decoupled structure of the resulting optimal control problem by using the conjugate gradient method for solving the nonlinear dynamic problem. Different examples of cost functionals are presented and the real-time capability is shown by applying this approach to a 9-DOF redundant manipulator.