Title
Multi-layered multi-pattern CPG for adaptive locomotion of humanoid robots
Abstract
In this paper, we present an extended mathematical model of the central pattern generator (CPG) in the spinal cord. The proposed CPG model is used as the underlying low-level controller of a humanoid robot to generate various walking patterns. Such biological mechanisms have been demonstrated to be robust in locomotion of animal. Our model is supported by two neurophysiological studies. The first study identified a neural circuitry consisting of a two-layered CPG, in which pattern formation and rhythm generation are produced at different levels. The second study focused on a specific neural model that can generate different patterns, including oscillation. This neural model was employed in the pattern generation layer of our CPG, which enables it to produce different motion patterns--rhythmic as well as non-rhythmic motions. Due to the pattern-formation layer, the CPG is able to produce behaviors related to the dominating rhythm (extension/flexion) and rhythm deletion without rhythm resetting. The proposed multi-layered multi-pattern CPG model (MLMP-CPG) has been deployed in a 3D humanoid robot (NAO) while it performs locomotion tasks. The effectiveness of our model is demonstrated in simulations and through experimental results.
Year
DOI
Venue
2014
10.1007/s00422-014-0592-8
Biological Cybernetics
Keywords
Field
DocType
Central pattern generator,Robot locomotion,Humanoid walking
Control theory,Neurophysiology,Control theory,CpG site,Robot locomotion,Central pattern generator,Biological neural network,Rhythm,Mathematics,Humanoid robot
Journal
Volume
Issue
ISSN
108
3
1432-0770
Citations 
PageRank 
References 
15
0.69
16
Authors
4
Name
Order
Citations
PageRank
John Nassour1344.35
Patrick Henaff27711.33
Fethi Ben Ouezdou3477.52
Gordon Cheng41250115.33