  In this paper, we present a Riemannian Motion Policy (RMP)flow-based
whole-body control framework for improved dynamic legged locomotion. RMPflow is
a differential geometry-inspired algorithm for fusing multiple task-space
policies (RMPs) into a configuration space policy in a geometrically consistent
manner. RMP-based approaches are especially suited for designing simultaneous
tracking and collision avoidance behaviors and have been successfully deployed
on serial manipulators. However, one caveat of RMPflow is that it is designed
with fully actuated systems in mind. In this work, we, for the first time,
extend it to the domain of dynamic-legged systems, which have unforgiving
under-actuation and limited control input. Thorough push recovery experiments
are conducted in simulation to validate the overall framework. We show that
expanding the valid stepping region with an RMP-based collision-avoidance swing
leg controller improves balance robustness against external disturbances by up
to 53\% compared to a baseline approach using a restricted stepping region.
Furthermore, a point-foot biped robot is purpose-built for experimental studies
of dynamic biped locomotion. A preliminary unassisted in-place stepping
experiment is conducted to show the viability of the control framework and
hardware.
