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A Developmental Learning Approach of Mobile Manipulator via Playing

Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The...

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Autores principales: Wu, Ruiqi, Zhou, Changle, Chao, Fei, Zhu, Zuyuan, Lin, Chih-Min, Yang, Longzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632655/
https://www.ncbi.nlm.nih.gov/pubmed/29046632
http://dx.doi.org/10.3389/fnbot.2017.00053
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author Wu, Ruiqi
Zhou, Changle
Chao, Fei
Zhu, Zuyuan
Lin, Chih-Min
Yang, Longzhi
author_facet Wu, Ruiqi
Zhou, Changle
Chao, Fei
Zhu, Zuyuan
Lin, Chih-Min
Yang, Longzhi
author_sort Wu, Ruiqi
collection PubMed
description Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode. By doing so, the robot gradually achieves it developmental goals by playing different modes of games. In the experiment, the game was instantiated into a mobile robot with the playing task of picking up toys, and the game is designed with a simple game mode and a complex game mode. A developmental algorithm, “Lift-Constraint, Act and Saturate,” is employed to drive the mobile robot move from the simple mode to the complex one. The experimental results show that the mobile manipulator is able to successfully learn the mobile grasping ability after playing simple and complex games, which is promising in developing robotic abilities to solve complex tasks using games.
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spelling pubmed-56326552017-10-18 A Developmental Learning Approach of Mobile Manipulator via Playing Wu, Ruiqi Zhou, Changle Chao, Fei Zhu, Zuyuan Lin, Chih-Min Yang, Longzhi Front Neurorobot Neuroscience Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode. By doing so, the robot gradually achieves it developmental goals by playing different modes of games. In the experiment, the game was instantiated into a mobile robot with the playing task of picking up toys, and the game is designed with a simple game mode and a complex game mode. A developmental algorithm, “Lift-Constraint, Act and Saturate,” is employed to drive the mobile robot move from the simple mode to the complex one. The experimental results show that the mobile manipulator is able to successfully learn the mobile grasping ability after playing simple and complex games, which is promising in developing robotic abilities to solve complex tasks using games. Frontiers Media S.A. 2017-10-04 /pmc/articles/PMC5632655/ /pubmed/29046632 http://dx.doi.org/10.3389/fnbot.2017.00053 Text en Copyright © 2017 Wu, Zhou, Chao, Zhu, Lin and Yang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Wu, Ruiqi
Zhou, Changle
Chao, Fei
Zhu, Zuyuan
Lin, Chih-Min
Yang, Longzhi
A Developmental Learning Approach of Mobile Manipulator via Playing
title A Developmental Learning Approach of Mobile Manipulator via Playing
title_full A Developmental Learning Approach of Mobile Manipulator via Playing
title_fullStr A Developmental Learning Approach of Mobile Manipulator via Playing
title_full_unstemmed A Developmental Learning Approach of Mobile Manipulator via Playing
title_short A Developmental Learning Approach of Mobile Manipulator via Playing
title_sort developmental learning approach of mobile manipulator via playing
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632655/
https://www.ncbi.nlm.nih.gov/pubmed/29046632
http://dx.doi.org/10.3389/fnbot.2017.00053
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