Learning of Motion Generation for Various Situations based on Sequence-to-Sequence Models

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DOI[10.24561/00019148]to the data of the same series

Learning of Motion Generation for Various Situations based on Sequence-to-Sequence Models

Persistent ID (NDL): info:ndljp/pid/11659385

Material type: 博士論文

Author: 沓澤, 京

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Publication date: 2020

Material Format: Digital

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Name of awarding university/degree: 埼玉大学,博士(工学)

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Note (General)：: type:text1 Introduction 5 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Issue . . . . . . . . . . . . ....

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Material Type: 博士論文
Title: Learning of Motion Generation for Various Situations based on Sequence-to-Sequence Models
Author/Editor: 沓澤, 京
Author Heading: 沓澤, 京
Publication Date: 2020
Publication Date (W3CDTF): 2020
Alternative Title: Sequence-to-Sequenceモデルに基づく多様な状況への動作生成の学習
Periodical title: 博士論文（埼玉大学大学院理工学研究科（博士後期課程））
Degree grantor/type: 埼玉大学
Date Granted: 2020-03-23
Date Granted (W3CDTF): 2020-03-23
Dissertation Number: 甲第1165号
Degree Type: 博士(工学)
Conferring No. (Dissertation): 甲第1165号
Text Language Code: eng
Target Audience: 一般
Note (General): type:text
1 Introduction 5 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.4 Seq2seq Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.5 Research Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.6 Construction of this Dissertation . . . . . . . . . . . . . . . . . . . . . . . . 92 Training of Seq2seq Models under Dynamic Constraints 11 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2.1 Physics Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2.2 Seq2seq Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2.3 Proposed Learning Curriculum . . . . . . . . . . . . . . . . . . . . . 15 2.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.1 Implementation of Seq2seq Model . . . . . . . . . . . . . . . . . . . 16 2.3.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.3 Experimental Result . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Training of Seq2seq Models under Discontinuous Dynamics 23 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2 Sequence-to-Sequence Model for Sliding Manipulation . . . . . . . . . . . . 24 3.2.1 Physics Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.2.2 Seq2seq Model Architecture . . . . . . . . . . . . . . . . . . . . . . . 25 3.3 Training Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.1 Objective Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.2 Training Strategy Based on Curriculum Learning . . . . . . . . . . . 27 3.4 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.4.1 Implementation of Seq2seq Model . . . . . . . . . . . . . . . . . . . 28 3.4.2 Implementation of Training . . . . . . . . . . . . . . . . . . . . . . . 29 3.5 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.5.1 Implementation of Simulation . . . . . . . . . . . . . . . . . . . . . . 30 3.5.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 Association of Latent Representations with External Orders by Mathematical Expressions 37 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.2.1 Issue to be Addressed . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.2.2 Optimization of the Latent Representation . . . . . . . . . . . . . . 39 4.2.3 Optimization Procedure . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3.1 Implementation of Seq2seq Model . . . . . . . . . . . . . . . . . . . 41 4.3.2 Adjusting Trajectories to Reach the Given End Positions . . . . . . 41 4.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.4.1 Setup of the Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.4.2 Trajectory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.4.3 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455 Association of Latent Representations with External Orders by Numerical Expressions 53 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.2.1 LfD using SeqAE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.1 Task Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.2 Control System Setup . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.3.3 Training-Data Collection . . . . . . . . . . . . . . . . . . . . . . . . 58 5.3.4 Model Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.3.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 5.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 646 Conclusion 67
指導教員 : 辻俊明
DOI: 10.24561/00019148
https://doi.org/10.24561/00019148
Persistent ID (NDL): info:ndljp/pid/11659385
https://dl.ndl.go.jp/pid/11659385
Collection: 障害者向け資料
Collection (Materials For Handicapped People:1): テキストデータ
Collection (particular): 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
https://dl.ndl.go.jp/collections/A00014
Acquisition Basis: 博士論文（自動収集）
Date Accepted (W3CDTF): 2021-04-07T03:01:57+09:00
Date Created (W3CDTF): 2021-01-26
Format (IMT): application/pdf
Access Restrictions: 国立国会図書館内限定公開
Service for the Digitized Contents Transmission Service: 図書館・個人送信対象外
Availability of remote photoduplication service: 可
Periodical Title (URI): http://dx.doi.org/10.24561/00019148
http://id.nii.ac.jp/1586/00019148/
Data Provider (Database): 国立国会図書館 : 国立国会図書館デジタルコレクション
https://dl.ndl.go.jp