DocumentCode :
2143917
Title :
A Recurrent Neural Network Model for Lamprey-Like Robot Movement
Author :
Daya, Bassam ; Chahine, Marybelle ; Awad, R.
Author_Institution :
Inst. of Technol., Lebanese Univ., Saida, Lebanon
fYear :
2013
fDate :
27-29 Sept. 2013
Firstpage :
316
Lastpage :
321
Abstract :
One of the most important problems in controlling robot locomotion, is how to generate an online trajectory for robots with a large number of degrees of freedom. In this paper, we present a biomimetic approach which is based on Central Pattern Generator (CPG) inspired from the lamprey to solve this problem. CPG is a neural network found in animal and has the ability of producing rhythmic pattern without receiving rhythmic input. We used a recurrent neural network(RNN) to model the CPG and proposed the genetic algorithm to train the RNN to follow a predefined oscillatory pattern. It is furthermore demonstrated that recurrent neural networks do indeed exhibit oscillatory behavior and may in this way be used to imitate the function of the CPG responsible for locomotion in animate creatures.
Keywords :
biomimetics; genetic algorithms; legged locomotion; recurrent neural nets; CPG; RNN; animate creatures; biomimetic approach; central pattern generator; genetic algorithm; lamprey-like robot movement; online trajectory; oscillatory pattern; recurrent neural network model; rhythmic pattern; robot locomotion; Communication networks; Computational intelligence; Central pattern generators; Locomotion; Recurrent Neural networks; Robots; genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2013 5th International Conference on
Conference_Location :
Mathura
Type :
conf
DOI :
10.1109/CICN.2013.72
Filename :
6658007
Link To Document :
بازگشت