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Chaos : Perception-action map learning in controlled multiscroll systems applied to robot navigation

By Paolo Arena, Sebastiano De Fiore, Luigi Fortuna, and Luca Patané

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Book Id: WPLBN0002169301
Format Type: PDF eBook :
File Size: Serial Publication
Reproduction Date: 2 December 2008

Title: Chaos : Perception-action map learning in controlled multiscroll systems applied to robot navigation  
Author: Paolo Arena, Sebastiano De Fiore, Luigi Fortuna, and Luca Patané
Volume: Issue : December 2008
Language: English
Subject: Science, Physics, Natural Science
Collections: Periodicals: Journal and Magazine Collection, Chaos Collection
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Publication Date:
Publisher: American Institute of Physics

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Sebastiano De Fiore, Luigi Fortuna, And Luca Patan, P. A. (n.d.). Chaos : Perception-action map learning in controlled multiscroll systems applied to robot navigation. Retrieved from http://hawaiilibrary.net/


Description
Description: In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

 

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