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Modelling Early Infant Walking: Testing a Generic CPG Architecture on the NAO Humanoid
Högskolan i Skövde, Institutionen för kommunikation och information.
Högskolan i Skövde, Institutionen för kommunikation och information.
Högskolan i Skövde, Institutionen för kommunikation och information.
2011 (English)In: IEEE International Conference on Development and Learning (ICDL), 2011, IEEE conference proceedings , 2011, 1-6 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this article, a simple CPG network is shown to model early infant walking, in particular the onset of independent walking. The difference between early infant walking and early adult walking is addressed with respect to the underlying neurophysiology and evaluated according to gait attributes. Based on this, we successfully model the early infant walking gait on the NAO robot and compare its motion dynamics and performance to those of infants. Our model is able to capture the core properties of early infant walking. We identify differences in the morphologies between the robot and infant and the effect of this on their respective performance. In conclusion, early infant walking can be seen to develop as a function of the CPG network and morphological characteristics.

Place, publisher, year, edition, pages
IEEE conference proceedings , 2011. 1-6 p.
Series
IEEE International Conference on Development and Learning (ICDL), ISSN 2161-9476 ; Vol. 2
Keyword [en]
Early Walking, CPG, Morphology, Development, NAO
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-106778DOI: 10.1109/DEVLRN.2011.6037318ISI: 000297472300007Scopus ID: 2-s2.0-80055009067ISBN: 978-1-61284-989-8 (print)OAI: oai:DiVA.org:liu-106778DiVA: diva2:718787
Conference
The 2011 IEEE International Conference on Development and Learning, ICDL 2011; Frankfurt am Main; 24-27 August 2011, Category number CFP11294-ART; Code 87020
Available from: 2013-02-18 Created: 2014-05-22 Last updated: 2014-05-22
In thesis
1. Reinforcement Learning of Locomotion based on Central Pattern Generators
Open this publication in new window or tab >>Reinforcement Learning of Locomotion based on Central Pattern Generators
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Locomotion learning for robotics is an interesting and challenging area in which the movement capabilities of animals have been deeply investigated and acquired knowledge has been transferred into modelling locomotion on robots. What modellers are required to understand is what structure can represent locomotor systems in different animals and how such animals develop various and dexterous locomotion capabilities. Notwithstanding the depth of research in the area, modelling locomotion requires a deep rethinking.

In this thesis, based on the umbrella of embodied cognition, a neural-body-environment interaction is emphasised and regarded as the solution to locomotion learning/development. Central pattern generators (CPGs) are introduced in the first part (Chapter 2) to generally interpret the mechanism of locomotor systems in animals. With a deep investigation on the structure of CPGs and inspiration from human infant development, a layered CPG architecture with baseline motion generation and dynamics adaptation interfaces are proposed. In the second part, reinforcement learning (RL) is elucidated as a good method for dealing with locomotion learning from the perspectives of psychology, neuroscience and robotics (Chapter 4). Several continuous-space RL techniques (e.g. episodic natural actor critic, policy learning by weighting explorations with returns, continuous action space learning automaton are introduced for practical use (Chapter 3). With the knowledge of CPGs and RL, the architecture and concept of CPG-Actor-Critic is constructed. Finally, experimental work based on published papers is highlighted in a path of my PhD research (Chapter 5). This includes the implementation of CPGs and the learning on the NAO robot for crawling and walking. The implementation is also extended to test the generalizability to different morphologies (the ghostdog robot). The contribution of this thesis is discussed from two angles: the investigation of the CPG architecture and the implementation (Chapter 6).

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 71 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1602
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-105884 (URN)978-91-7519-313-7 (ISBN)
Public defence
2014-06-04, G110, hus G, Högskolan i Skövde, Skövde, 12:30 (English)
Opponent
Supervisors
Available from: 2014-05-22 Created: 2014-04-11 Last updated: 2014-05-22Bibliographically approved

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Lee, GaussLowe, RobertZiemke, Tom

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CiteExportLink to record
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Citation style
  • apa
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