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An Empirical Exploration of a Neural Oscillator for Biped Locomotion Control
 

Summary: An Empirical Exploration of a Neural Oscillator
for Biped Locomotion Control
Gen Endo 2,1
, Jun Morimoto 2
, Jun Nakanishi 3,2
and Gordon Cheng 2
Abstract-- Humanoid research has made remarkable progress
during the past 10 years. However, currently most humanoids
use the target ZMP (Zero Moment Point) control algorithm for
bipedal locomotion, which requires precise modeling and
actuation with high control gains. On the contrary, humans do
not rely on such precise modeling and actuation. Our aim is to
examine biologically related algorithms for bipedal locomotion
that resemble human-like locomotion. This paper describes an
empirical study of a neural oscillator for the control of biped
locomotion. We propose a new neural oscillator arrangement
applied to a compass-like biped robot. Dynamic simulations and
experiments with a real biped robot were carried out and the
controller performs steady walking for over 50 steps. Gait
variations resulting in energy efficiency was made possible

  

Source: Atkeson, Christopher G. - Robotics Institute, School of Computer Science, Carnegie Mellon University
Zeglin, Garth - Robotics Institute, Carnegie Mellon University

 

Collections: Computer Technologies and Information Sciences; Engineering