Paper Info
Title
Evolved Center-Crossing Recurrent Synaptic Delay Based Neural Networks For Biped Locomotion Control
Abstract
This paper combines the center-crossing condition in artificial neural networks that incorporate synaptic delays in their connections and which act as Central Pattern Generators (CPGs) for biped controllers. Recurrent synaptic delay based neural networks allow greater time reasoning capabilities in the neural controllers, outperforming the results of continuous time recurrent neural networks, the neural model most used as CPG for biped robot locomotion related behaviors. Simulated evolution is used to automatically obtain neural controllers for walking behaviors, showing the capabilities of the synaptic delay based neural networks for the temporal coordination of the biped joints in difficult surfaces.
Year
DOI
Venue
2013
10.1109/CEC.2013.6557564
2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Keywords
Field
DocType
Synaptic delay based neural networks, continuous time recurrent ANNs, center-crossing ANNs, evolutionary robotics
Recurrent neural nets,Physical neural network,Computer science,Recurrent neural network,Time delay neural network,Gait analysis,Robot locomotion,Artificial intelligence,Artificial neural network,Central pattern generator,Machine learning
Conference
Citations 
PageRank 
References 
2
0.39
0
Authors
1
Name
Order
Citations
PageRank
José Santos19714.77