NDLI: A neural network with central pattern generators entrained by sensory feedback controls walking of a bipedal model

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A neural network with central pattern generators entrained by sensory feedback controls walking of a bipedal model

Content Provider	Scilit
Author	Li, Wei Szczecinski, Nicholas S. Quinn, Roger D.
Copyright Year	2017
Description	Journal: Bioinspiration & Biomimetics A neuromechanical simulation of a planar, bipedal walking robot has been developed. It is constructed as a simplified, planar musculoskeletal model of the biomechanics of the human lower body. The controller consists of a dynamic neural network with central pattern generators (CPGs) entrained by force and movement sensory feedback to generate appropriate muscle forces for walking. The CPG model is a two-level architecture, which consists of separate rhythm generator and pattern formation networks. The biped model walks stably in the sagittal plane without inertial sensors or a centralized posture controller or a 'baby walker' to help overcome gravity. Its gait is similar to humans' and it walks at speeds from 0.850 m $s^{−1}$ up to 1.289 m $s^{−1}$ with leg length of 0.84 m. The model walks over small unknown steps (6% of leg length) and up and down 5° slopes without any additional higher level control actions.
Related Links	http://iopscience.iop.org/article/10.1088/1748-3190/aa8290/ampdf http://iopscience.iop.org/article/10.1088/1748-3190/aa8290/pdf
ISSN	17483182
e-ISSN	17483190
DOI	10.1088/1748-3190/aa8290
Journal	Bioinspiration & Biomimetics
Issue Number	6
Volume Number	12
Language	English
Publisher	IOP Publishing
Publisher Date	2017-10-16
Access Restriction	Open
Subject Keyword	Journal: Bioinspiration & Biomimetics Bipedal Walking Central Pattern Generator Neural Controller Neuromechanical Simulation
Content Type	Text
Resource Type	Article
Subject	Medicine Biochemistry Biophysics Engineering Molecular Medicine Biotechnology

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