Biologically-inspired adaptive dynamic walking of the quadruped on irregular terrain

We attempt to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. We propose the biologically-inspired control method consisting of four levels: adaptive control using a muscle stiffness model; adaptive control based on vestibular sensation; parameters adjustment based on somatic sensation and reflexes coordination based on vestibular sensation; and motion switching based on visual information. From the experiments, we show that a robot can walk on a single bump and up a slope by using such adaptive control method. We also show that the functions as a lower controller in the Drew's physiological model for leg control mechanism based on visual information are satisfied by a CPG characterized by mutual entrainment with a musculo-skeletal system, automatic interpolation, and self stabilization. These findings suggest a simple method for producing autonomous adaptive dynamic walking on terrain of high degree irregularity.

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