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Advances in legged robotics are strongly rooted in animal observations. Aclear illustration of this claim is the generalization of Central PatternGenerators (CPG), first identified in the cat spinal cord, to generate cyclicmotion in robotic locomotion. Despite a global endorsement of this model,physiological and functional experiments in mammals have also indicated thepresence of descending signals from the cerebellum, and reflex feedback fromthe lower limb sensory cells, that closely interact with CPGs. To this day,these interactions are not fully understood. In some studies, it wasdemonstrated that pure reflex-based locomotion in the absence of oscillatorysignals could be achieved in realistic musculoskeletal simulation models orsmall compliant quadruped robots. At the same time, biological evidence hasattested the functional role of the cerebellum for predictive control ofbalance and stance within mammals. In this paper, we promote both approachesand successfully apply reflex-based dynamic locomotion, coupled with a balanceand gravity compensation mechanism, on the state-of-art HyQ robot. We discussthe importance of this stability module to ensure a correct foot lift-off andmaintain a reliable gait. The robotic platform is further used to test twodifferent architectural hypotheses inspired by the cerebellum. An analysis ofexperimental results demonstrates that the most biologically plausiblealternative also leads to better results for robust locomotion.

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot