creators_name: Cangelosi, Angelo
creators_name: Massera, Gianluca
creators_name: Nolfi, Stefano
creators_id: acangelosi@plymouth.ac.uk
type: journalp
datestamp: 2008-10-22 01:17:40
lastmod: 2011-03-11 08:57:13
metadata_visibility: show
title: Evolution of Prehension Ability in an Anthropomorphic Neurorobotic Arm
ispublished: pub
subjects: neuro-mod
subjects: comp-sci-mach-dynam-sys
subjects: comp-sci-robot
subjects: comp-sci-neural-nets
subjects: comp-sci-art-intel
full_text_status: public
keywords: Robotic arm, reaching and grasping, adaptation, evolutionary robotics
abstract: In this paper we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot’s body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators, and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.
date: 2007-11
date_type: published
publication: Frontiers in Neurorobotics
volume: 1
number: 4
refereed: TRUE
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citation:   Cangelosi, Prof Angelo and Massera, Gianluca and Nolfi, Stefano  (2007) Evolution of Prehension Ability in an Anthropomorphic Neurorobotic Arm.  [Journal (Paginated)]     
document_url: http://cogprints.org/6237/1/massera_cangelosi_nolfi_Frontiers.pdf