  In this paper, we devise methods for the multi- objective control of humanoid
robots, a.k.a. prioritized whole- body controllers, that achieve efficiency and
robustness in the algorithmic computations. We use a form of whole-body
controllers that is very general via incorporating centroidal momentum
dynamics, operational task priorities, contact re- action forces, and internal
force constraints. First, we achieve efficiency by solving a quadratic program
that only involves the floating base dynamics and the reaction forces. Second,
we achieve computational robustness by relaxing task accelerations such that
they comply with friction cone constraints. Finally, we incorporate methods for
smooth contact transitions to enhance the control of dynamic locomotion
behaviors. The proposed methods are demonstrated both in simulation and in real
experiments using a passive-ankle bipedal robot.
