Active categorical perception in an evolved anthropomorphic robotic arm

Elio Tuci, Gianluca Massera, Stefano Nolfi

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

6 Citations (SciVal)
166 Downloads (Pure)

Abstract

Active perception refers to a theoretical approach to the study of perception grounded on the idea that perceiving is a way of acting, rather than a cognitive process whereby the brain constructs an internal representation of the world. The operational principles of active perception can be effectively tested by building robot-based models in which the relationship between perceptual categories and the body-environment interactions can be experimentally manipulated. In this paper, we study the mechanisms of tactile perception in a task in which a neuro-controlled anthropomorphic robotic arm, equipped with coarse-grained tactile sensors, is required to perceptually discriminate between spherical and ellipsoid objects. The results of this work demonstrate that evolved continuous time nonlinear neural controllers can bring forth strategies to allow the arm to effectively solve the discrimination task.
Original languageEnglish
Title of host publicationProc. of the IEEE International Conference on Evolutionary Computation (CEC), special session on Evolutionary Robotics
Pages978-1
Number of pages8
Publication statusPublished - 18 May 2009
EventIEEE International Conference on Evolutionary Computation (CEC) - Trondheim, Norway
Duration: 18 May 200921 May 2009

Conference

ConferenceIEEE International Conference on Evolutionary Computation (CEC)
Country/TerritoryNorway
CityTrondheim
Period18 May 200921 May 2009

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