  This paper demonstrates simultaneous identification and control of the
humanoid robot, Valkyrie, utilizing Spatial Vector Algebra (SVA). In
particular, the inertia, Coriolis-centrifugal and gravity terms for the
dynamics of a robot are computed using spatial inertia tensors. With the
assumption that the link lengths or the distance between the joint axes are
accurately known, it will be shown that inertial properties of a robot can be
directly evaluated from the inertia tensor. An algorithm is proposed to
evaluate the regressor, yielding a run time of $O(n^2)$. The efficiency of this
algorithm yields a means for online system identification via the SVA--based
regressor and, as a byproduct, a method for accurate model-based control.
Experimental validation of the proposed method is provided through its
implementation in three case studies: offline identification of a double
pendulum and a $4$-DOF robotic leg, and online identification and control of a
$4$-DOF robotic arm.
