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Developmental Approach for Behavior Learning Using Primitive Motion Skills

Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative...

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Main Authors: Dawood, Farhan, Loo, Chu Kiong
Format: Article
Published: World Scientific Publishing 2018
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
Online Access:http://eprints.um.edu.my/22153/
https://doi.org/10.1142/S0129065717500381
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spelling my.um.eprints.221532019-08-30T04:04:48Z http://eprints.um.edu.my/22153/ Developmental Approach for Behavior Learning Using Primitive Motion Skills Dawood, Farhan Loo, Chu Kiong QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: Automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatiooral motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot. World Scientific Publishing 2018 Article PeerReviewed Dawood, Farhan and Loo, Chu Kiong (2018) Developmental Approach for Behavior Learning Using Primitive Motion Skills. International Journal of Neural Systems, 28 (04). p. 1750038. ISSN 0129-0657 https://doi.org/10.1142/S0129065717500381 doi:10.1142/S0129065717500381
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
Dawood, Farhan
Loo, Chu Kiong
Developmental Approach for Behavior Learning Using Primitive Motion Skills
description Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: Automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatiooral motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.
format Article
author Dawood, Farhan
Loo, Chu Kiong
author_facet Dawood, Farhan
Loo, Chu Kiong
author_sort Dawood, Farhan
title Developmental Approach for Behavior Learning Using Primitive Motion Skills
title_short Developmental Approach for Behavior Learning Using Primitive Motion Skills
title_full Developmental Approach for Behavior Learning Using Primitive Motion Skills
title_fullStr Developmental Approach for Behavior Learning Using Primitive Motion Skills
title_full_unstemmed Developmental Approach for Behavior Learning Using Primitive Motion Skills
title_sort developmental approach for behavior learning using primitive motion skills
publisher World Scientific Publishing
publishDate 2018
url http://eprints.um.edu.my/22153/
https://doi.org/10.1142/S0129065717500381
_version_ 1643691762401673216
score 13.211869

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