  The increasing interest in autonomous robots with a high number of degrees of
freedom for industrial applications and service robotics demands control
algorithms to handle multiple tasks as well as hard constraints efficiently.
This paper presents a general framework in which both kinematic (velocity- or
acceleration-based) and dynamic (torque-based) control of redundant robots are
handled in a unified fashion. The framework allows for the specification of
redundancy resolution problems featuring a hierarchy of arbitrary (equality and
inequality) constraints, arbitrary weighting of the control effort in the cost
function and an additional input used to optimize possibly remaining
redundancy. To solve such problems, a generalization of the Saturation in the
Null Space (SNS) algorithm is introduced, which extends the original method
according to the features required by our general control framework. Variants
of the developed algorithm are presented, which ensure both efficient
computation and optimality of the solution. Experiments on a KUKA LBRiiwa
robotic arm, as well as simulations with a highly redundant mobile manipulator
are reported.
