Authors:
Rodrigo R. Braga
1
;
Zhijun Yang
2
and
Felipe M. G. França
3
Affiliations:
1
Federal University of Rio de Janeiro, Brazil
;
2
School of Engineering and Electronics, Edinburgh University, United Kingdom
;
3
Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, Brazil
Keyword(s):
Centipede locomotion, central pattern generator, distributed algorithms, post-inhibitory rebound, scheduling by multiple edge reversal.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
In nature, a high number of species seems to have purely inhibitory neuronal networks called Central Pattern Generators (CPGs), allowing them to produce biological rhythmic patterns in the absence of any external input. It is believed that one of the mechanisms behind CPGs functioning is the Post-Inhibitory Rebound (PIR) effect. Based in the similarity between the PIR functioning and the Scheduled by Multiple Edge Reversal (SMER) distributed synchronizer algorithm, a generalized architecture for the construction of artificial CPGs was proposed. In this work, this architecture was generalized by integrating, in a single model, the axial and appendicular movements of a centipede in the fastest gait pattern of locomotion.