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Please use this identifier to cite or link to this item: http://hdl.handle.net/10445/5282

Title: Embedded Neural Network for Learning of Physical Robots
Authors: Hartono, Pitoyo
Kakita, Sachiko
Abstract: In this study we ran real time learning of multiple physical autonomous robots situated in a real dynamic environment. Each robot has an onboard micro controller where a simple neural network is embedded. The neural network was built with the consideration of the power and calculation resources limitation which is a general characteristic of simple robots. In the experiments, several autonomous robots were placed in one environment, where each of them was given a specific task which was expressed as the evaluation function for the robot's neural network. The learning processes of the robots were started simultaneously from their randomized initial conditions. The presence of several robots consequently formed a dynamic environment, in which an action of one robot affected the learning process of others. We demonstrated the efficiency of the embedded learning mechanism with respect to different environmental factors.
Research Achievement Classification: 国際会議/International Conference
Type: Conference Paper
Peer Review: あり/yes
Solo/Joint Author(s): 共著/joint
Published journal or presented
academic conference: 
Proc. Int. Conf. on Artificial Neural Networks (ICANN 2008)
Volume: 2
Spage: 141
Epage: 149
Date: 2008
Publisher: Springer LNCS 5163
Appears in Collections:Pitoyo, Hartono

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