  We present a generalized version of the Saturation in the Null Space (SNS)
algorithm for the task control of redundant robots when hard inequality
constraints are simultaneously present both in the joint and in the Cartesian
space. These hard bounds should never be violated, are treated equally and in a
unified way by the algorithm, and may also be varied, inserted or deleted
online. When a joint/Cartesian bound saturates, the robot redundancy is
exploited to continue fulfilling the primary task. If no feasible solution
exists, an optimal scaling procedure is applied to enforce directional
consistency with the original task. Simulation and experimental results on
different robotic systems demonstrate the efficiency of the approach. The
proposed algorithm can be viewed as a generic platform that is easily
applicable to any robotic application in which robots operate in an
unstructured environment and online handling of joint and Cartesian constraints
is critical.
