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

From Human Walking to Bipedal Robot Locomotion: Reflex Inspired Compensation on Planned and Unplanned Downsteps