Synthetic evolution for wheeled robot cognition in RF-localization behavior

Kim, On Chin and Teo, Jason Tze Wi and Azali Saudi, (2009) Synthetic evolution for wheeled robot cognition in RF-localization behavior. In: 2009 International Conference on Future Computer and Communication, (ICFCC), 3-5 April 2009, Kuala Lumpur, Malaysia.

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Official URL: http://dx.doi.org/10.1109/ICFCC.2009.102

Abstract

This paper discussed the utilization of a multiobjective approach for evolving artificial neural networks (ANNs) that act as a controller for radio frequency (RF)-localization behavior of a virtual Khepera robot simulated in a 3D, physics-based environment. The Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal sets of ANNs that optimize the conflicting objectives of maximizing the virtual Khepera robot's behavior for homing towards a RF signal source and minimizing the number of hidden neurons used in its feed-forward ANNs controller. A fitness function used for mobile robot RFlocalization behavior is proposed. The experimentation results showed the virtual Khepera robot was able to navigate towards signal source with using only a small number of hidden neurons. Furthermore, the Pareto-frontier solutions have been utilized for robustness testing purposes in the environment differs as that used during evolution. The results showed the PDE-EMO algorithm can be practically used in generating the required robot controllers for RF-localization behavior. © 2009 IEEE.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Autonomous robot, Evolutionary multiobjective optimization (EMO), Evolutionary robotics (ER), Neural network
Subjects:?? TJ210.2-211.47 ??
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:2477
Deposited By:IR Admin
Deposited On:24 Mar 2011 17:08
Last Modified:30 Dec 2014 14:38

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