  Humans are able to negotiate downstep behaviors -- both planned and unplanned
-- with remarkable agility and ease. The goal of this paper is to
systematically study the translation of this human behavior to bipedal walking
robots, even if the morphology is inherently different. Concretely, we begin
with human data wherein planned and unplanned downsteps are taken. We analyze
this data from the perspective of reduced-order modeling of the human, encoding
the center of mass (CoM) kinematics and contact forces, which allows for the
translation of these behaviors into the corresponding reduced-order model of a
bipedal robot. We embed the resulting behaviors into the full-order dynamics of
a bipedal robot via nonlinear optimization-based controllers. The end result is
the demonstration of planned and unplanned downsteps in simulation on an
underactuated walking robot.
