Evolution of Synaptic Delay Based Neural Controllers for Implementing Central Pattern Generators in Hexapod Robotic Structures

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9108)

Abstract

We used synaptic delay based neural networks for implementing Central Pattern Generators (CPGs) for locomotion behaviors in hexapod robotic structures. These networks incorporate synaptic delays in their connections which allow greater time reasoning capabilities in the neural controllers, and additionally we incorporated the concept of the center-crossing condition in such networks to facilitate obtaining oscillation patterns for the robotic control. We compared the results against continuous time recurrent neural networks, one of the neural models most used as CPG, when proprioceptive information is used to provide fault tolerance for the required behavior.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Computer Science DepartmentUniversity of A CoruñaA CoruñaSpain

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