1 research outputs found
Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot
Advances in legged robotics are strongly rooted in animal observations. A
clear illustration of this claim is the generalization of Central Pattern
Generators (CPG), first identified in the cat spinal cord, to generate cyclic
motion in robotic locomotion. Despite a global endorsement of this model,
physiological and functional experiments in mammals have also indicated the
presence of descending signals from the cerebellum, and reflex feedback from
the lower limb sensory cells, that closely interact with CPGs. To this day,
these interactions are not fully understood. In some studies, it was
demonstrated that pure reflex-based locomotion in the absence of oscillatory
signals could be achieved in realistic musculoskeletal simulation models or
small compliant quadruped robots. At the same time, biological evidence has
attested the functional role of the cerebellum for predictive control of
balance and stance within mammals. In this paper, we promote both approaches
and successfully apply reflex-based dynamic locomotion, coupled with a balance
and gravity compensation mechanism, on the state-of-art HyQ robot. We discuss
the importance of this stability module to ensure a correct foot lift-off and
maintain a reliable gait. The robotic platform is further used to test two
different architectural hypotheses inspired by the cerebellum. An analysis of
experimental results demonstrates that the most biologically plausible
alternative also leads to better results for robust locomotion