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A novel approach to...
A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives
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- Li, Cai (författare)
- Högskolan i Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi,Interaction Lab,University of Skovde, Sweden
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- Lowe, Robert (författare)
- Högskolan i Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi,Interaction Lab,University of Skovde, Sweden
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- Ziemke, Tom (författare)
- Högskolan i Skövde,Linköpings universitet,Interaktiva och kognitiva system,Tekniska högskolan,University of Skovde, Sweden,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi,Department of Computer and Information Science, Linköping University, Sweden,Interaction Lab
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(creator_code:org_t)
- 2014-10-02
- 2014
- Engelska.
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Ingår i: Frontiers in Neurorobotics. - : Frontiers. - 1662-5218. ; 8
- Relaterad länk:
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https://www.frontier...
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https://doi.org/10.3...
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http://www.ncbi.nlm....
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Abstract
Ämnesord
Stäng
- In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding a good "reshaping" function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Nyckelord
- actor-critic; central pattern generators (CPG); reinforcement learning; locomotion control; NAO robot
- Interaction Lab (ILAB)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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