Faculty Profiles - NAKAMURA Takayuki

写真a

NAKAMURA Takayuki

Name of department

Faculty of Systems Engineering, Intelligent Informatics

Job title

Professor

Concurrent post

Informatics Division（Professor）

Mail Address

Homepage

External link

Education

-

1996

Osaka University Graduate School of Engineering 電子制御機械工学専攻（博士後期課程修了）
-

1993

Osaka University Graduate School of Engineering 電子制御機械工学専攻（博士前期課程修了）
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1991

Osaka University School of Engineering 機械工学科卒業

Degree

博士（工学）

Academic & Professional Experience

2013.04

-

Now

和歌山大学システム工学部教授
2006.04

-

2013.03

Wakayama University Faculty of Systems Engineering 准教授
2002.04

-

2006.03

和歌山大学システム工学部助教授
1999

-

2001

科学技術振興事業団北野共生システムプロジェクト研究推進委員
1997.04

-

2002.03

奈良先端科学技術大学院大学情報科学研究科助手
1996

-

1997

米国ブラウン大学計算機科学科客員研究員
1996

-

1997

日本学術振興会特別研究員(PD数物系2342)

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Association Memberships

日本機械学会
日本ロボット学会
計測自動制御学会

Research Areas

Informatics / Intelligent informatics
Informatics / Robotics and intelligent systems
Informatics / Perceptual information processing
Informatics / Intelligent robotics
Informatics / Mechanics and mechatronics

Classes (including Experimental Classes, Seminars, Graduation Thesis Guidance, Graduation Research, and Topical Research)

2022 Introduction to Intelligent Robots Specialized Subjects
2022 Intelligent Informatics Seminar Specialized Subjects
2022 Logic Circuit Specialized Subjects
2022 Fundamentals of Robotics Liberal Arts and Sciences Subjects
2022 Graduation Research Specialized Subjects
2021 Logic Circuit Specialized Subjects
2021 Intelligent Informatics Seminar Specialized Subjects
2021 Introduction to Intelligent Robots Specialized Subjects
2021 Graduation Research Specialized Subjects
2021 Graduation Research Specialized Subjects
2021 Introductory Seminar in Systems Engineering Specialized Subjects
2021 Fundamentals of Robotics Liberal Arts and Sciences Subjects
2020 Fundamentals of Robotics Liberal Arts and Sciences Subjects
2020 Graduation Research Specialized Subjects
2020 Graduation Research Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Introductory Seminar in Systems Engineering Specialized Subjects
2020 Intelligent Informatics Seminar Specialized Subjects
2020 Introduction to Intelligent Robots Specialized Subjects
2020 Exercises in Majors E Specialized Subjects
2020 Exercises in Majors D Specialized Subjects
2020 Exercises in Majors C Specialized Subjects
2020 Exercises in Majors B Specialized Subjects
2020 Exercises in Majors A Specialized Subjects
2020 Introduction to Majors 2 Specialized Subjects
2020 Introduction to Majors 2 Specialized Subjects
2020 Introduction to Majors 1 Specialized Subjects
2020 Introduction to Majors 1 Specialized Subjects
2020 Logic Circuit Specialized Subjects
2019 Intelligent Informatics Seminar Specialized Subjects
2019 Introduction to Intelligent Robots Specialized Subjects
2019 Exercises in Majors C Specialized Subjects
2019 Exercises in Majors B Specialized Subjects
2019 Exercises in Majors A Specialized Subjects
2019 Introduction to Majors 2 Specialized Subjects
2019 Introduction to Majors 2 Specialized Subjects
2019 Introduction to Majors 1 Specialized Subjects
2019 Introduction to Majors 1 Specialized Subjects
2019 Introductory Seminar in Systems Engineering Specialized Subjects
2019 Logic Circuit Specialized Subjects
2018 Graduation Research Specialized Subjects
2018 Intelligent Informatics Seminar Specialized Subjects
2018 Introduction to Intelligent Robots Specialized Subjects
2018 Introductory Seminar in Systems Engineering Specialized Subjects
2018 Logic Circuit Specialized Subjects
2017 Computer and Communication Sciences Seminar Specialized Subjects
2017 Graduation Research Specialized Subjects
2017 Introduction to Intelligent Robots Specialized Subjects
2017 Logic Circuit Specialized Subjects
2016 Graduation Research Specialized Subjects
2016 Basic Robotics Specialized Subjects
2016 Computer and Communication Sciences Seminar Specialized Subjects
2016 Logic Circuit Specialized Subjects
2015 Graduation Research Specialized Subjects
2015 Basic Robotics Specialized Subjects
2015 Voluntary Study on Systems Engineering Ⅴ Specialized Subjects
2015 Logic Circuit Specialized Subjects
2015 Graduation Research Specialized Subjects
2015 Computer and Communication Sciences Seminar Specialized Subjects
2014 Graduation Research Specialized Subjects
2014 Graduation Research Specialized Subjects
2014 Basic Robotics Specialized Subjects
2014 Computer and Communication Sciences Seminar Specialized Subjects
2014 Computer and Communication SciencesApplied Experiment Specialized Subjects
2014 Logic Circuit Specialized Subjects
2014 Introduction to Computer and Communication Sciences Specialized Subjects
2014 Introduction to information science Liberal Arts and Sciences Subjects
2014 Graduation Research Specialized Subjects
2014 Introduction to Computer and Communication Sciences Specialized Subjects
2014 Computer and Communication SciencesApplied Experiment Specialized Subjects
2014 Basic Robotics Specialized Subjects
2013 Graduation Research Specialized Subjects
2013 Graduation Research Specialized Subjects
2013 Voluntary Study on Systems Engineering Ⅰ Specialized Subjects
2013 Basic Robotics Specialized Subjects
2013 Computer and Communication Sciences Seminar Specialized Subjects
2013 Computer and Communication SciencesApplied Experiment Specialized Subjects
2013 Logic Circuit Specialized Subjects
2013 Introduction to Computer and Communication Sciences Specialized Subjects
2013 Introduction to information science Liberal Arts and Sciences Subjects
2013 Introductory Seminar Liberal Arts and Sciences Subjects
2012 Graduation Research Specialized Subjects
2012 Introduction to Computer and Communication Sciences Specialized Subjects
2012 Basic Robotics Specialized Subjects
2012 Logic Circuit Specialized Subjects
2012 Graduation Research Specialized Subjects
2012 Computer and Communication SciencesApplied Experiment Specialized Subjects
2012 Computer and Communication Sciences Seminar Specialized Subjects
2012 Introduction to information science Liberal Arts and Sciences Subjects
2011 Introductory Seminar Liberal Arts and Sciences Subjects
2011 NA Liberal Arts and Sciences Subjects
2011 Graduation Research Specialized Subjects
2011 Basic Robotics Specialized Subjects
2011 Logic Circuit Specialized Subjects
2011 Computer and Communication SciencesApplied Experiment Specialized Subjects
2011 Computer and Communication Sciences Seminar Specialized Subjects
2011 Graduation Research Specialized Subjects
2011 Voluntary Study on Systems Engineering Ⅴ Specialized Subjects
2011 Computer and Communication Sciences Seminar Specialized Subjects
2011 Computer and Communication SciencesApplied Experiment Specialized Subjects
2011 Introductory Seminar Liberal Arts and Sciences Subjects
2011 Modern Information Technology Specialized Subjects
2011 Basic Robotics Specialized Subjects
2011 Logic Circuit Specialized Subjects
2011 Introduction to Computer and Communication Sciences Specialized Subjects
2011 Introduction to information science Liberal Arts and Sciences Subjects
2010 Logic Circuit Specialized Subjects
2010 Basic Robotics Specialized Subjects
2010 Computer and Communication SciencesApplied Experiment Specialized Subjects
2010 Computer and Communication Sciences Seminar Specialized Subjects
2010 Introduction to Computer and Communication Sciences Specialized Subjects
2010 Graduation Research Specialized Subjects
2010 NA Specialized Subjects
2009 Introduction to information science Liberal Arts and Sciences Subjects
2009 Computer and Communication Sciences Seminar Specialized Subjects
2009 Computer and Communication SciencesApplied Experiment Specialized Subjects
2009 Basic Robotics Specialized Subjects
2009 Logic Circuit Specialized Subjects
2009 Introduction to Computer and Communication Sciences Specialized Subjects
2009 Graduation Research Specialized Subjects
2008 Computer and Communication SciencesApplied Experiment Specialized Subjects
2008 Computer and Communication Sciences Seminar Specialized Subjects
2008 Basic Robotics Specialized Subjects
2008 Logic Circuit Specialized Subjects
2008 Introduction to Computer and Communication Sciences Specialized Subjects
2008 Graduation Research Specialized Subjects
2008 Introductory Seminar Specialized Subjects
2008 NA Liberal Arts and Sciences Subjects
2007 Computer and Communication Sciences Seminar Specialized Subjects
2007 Basic Robotics Specialized Subjects
2007 Introduction to Computer and Communication Sciences Specialized Subjects
2007 Graduation Research Specialized Subjects
2007 NA Liberal Arts and Sciences Subjects

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Independent study

2014 Raspberry Piを用いた遠隔水やり器の開発
2013 マイコン(mbed)とWiiヌンチャクを用いたロボット操作インターフェースの製作I（前期）
2013 マイコン(mbed)とWiiヌンチャクを用いたロボット操作インターフェースの製作II（後期）
2012 電動車椅子のコンピュータ制御に関する研究
2011 電動車椅子制御用RTCコンポーネントの作成
2010 LCMを用いたカメラヘッドシステムの作成
2009 Linuxを用いたラジコンサーボモーターの制御

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Classes

2022 Systems Engineering Global Seminar Ⅱ Doctoral Course
2022 Systems Engineering Global Seminar Ⅰ Doctoral Course
2022 Systems Engineering Advanced Research Doctoral Course
2022 Systems Engineering Advanced Seminar Ⅱ Doctoral Course
2022 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2022 Systems Engineering Project SeminarⅡB Master's Course
2022 Systems Engineering Project SeminarⅡA Master's Course
2022 Systems Engineering Project SeminarⅠB Master's Course
2022 Systems Engineering Project SeminarⅠA Master's Course
2022 Systems Engineering SeminarⅡB Master's Course
2022 Systems Engineering SeminarⅡA Master's Course
2022 Systems Engineering SeminarⅠB Master's Course
2022 Systems Engineering SeminarⅠA Master's Course
2022 AI-based Robotics Master's Course
2021 Systems Engineering Global Seminar Ⅱ Doctoral Course
2021 Systems Engineering Global Seminar Ⅰ Doctoral Course
2021 Systems Engineering Advanced Research Doctoral Course
2021 Systems Engineering Advanced Seminar Ⅱ Doctoral Course
2021 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2021 Systems Engineering Project SeminarⅡB Master's Course
2021 Systems Engineering Project SeminarⅡA Master's Course
2021 Systems Engineering Project SeminarⅠB Master's Course
2021 Systems Engineering Project SeminarⅠA Master's Course
2021 Systems Engineering SeminarⅡB Master's Course
2021 Systems Engineering SeminarⅡA Master's Course
2021 Systems Engineering SeminarⅠB Master's Course
2021 Systems Engineering SeminarⅠA Master's Course
2021 AI-based Robotics Master's Course
2020 Systems Engineering Global Seminar Ⅱ Doctoral Course
2020 Systems Engineering Global Seminar Ⅰ Doctoral Course
2020 Systems Engineering Advanced Research Doctoral Course
2020 Systems Engineering Advanced Seminar Ⅱ Doctoral Course
2020 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2020 Systems Engineering Project SeminarⅡB Master's Course
2020 Systems Engineering Project SeminarⅡA Master's Course
2020 Systems Engineering Project SeminarⅠB Master's Course
2020 Systems Engineering Project SeminarⅠA Master's Course
2020 Systems Engineering SeminarⅡB Master's Course
2020 Systems Engineering SeminarⅡA Master's Course
2020 Systems Engineering SeminarⅠB Master's Course
2020 Systems Engineering SeminarⅠA Master's Course
2020 AI-based Robotics Master's Course
2019 AI-based Robotics Master's Course
2019 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2019 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2019 Systems Engineering Advanced Research Doctoral Course
2019 Systems Engineering Advanced Research Doctoral Course
2019 Systems Engineering SeminarⅡB Master's Course
2019 Systems Engineering SeminarⅡA Master's Course
2019 Systems Engineering SeminarⅠB Master's Course
2019 Systems Engineering SeminarⅠA Master's Course
2019 Systems Engineering Project SeminarⅡB Master's Course
2019 Systems Engineering Project SeminarⅡA Master's Course
2019 Systems Engineering Project SeminarⅠB Master's Course
2019 Systems Engineering Project SeminarⅠA Master's Course
2018 Systems Engineering Global Seminar Ⅱ Doctoral Course
2018 Systems Engineering Global Seminar Ⅱ Doctoral Course
2018 Systems Engineering Advanced Research Doctoral Course
2018 Systems Engineering Advanced Research Doctoral Course
2018 Systems Engineering Project SeminarⅡB Master's Course
2018 Systems Engineering Project SeminarⅡA Master's Course
2018 Systems Engineering Project SeminarⅠB Master's Course
2018 Systems Engineering Project SeminarⅠA Master's Course
2018 Systems Engineering SeminarⅡB Master's Course
2018 Systems Engineering SeminarⅡA Master's Course
2018 Systems Engineering SeminarⅠB Master's Course
2018 Systems Engineering SeminarⅠA Master's Course
2018 AI-based Robotics Master's Course
2017 Systems Engineering Global Seminar Ⅱ Doctoral Course
2017 Systems Engineering Advanced Research Doctoral Course
2017 Systems Engineering Advanced Research Doctoral Course
2017 Systems Engineering Advanced Seminar Ⅱ Doctoral Course
2017 Systems Engineering Advanced Seminar Ⅱ Doctoral Course
2017 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2017 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2017 Systems Engineering Project SeminarⅡB Master's Course
2017 Systems Engineering Project SeminarⅡA Master's Course
2017 Systems Engineering Project SeminarⅠB Master's Course
2017 Systems Engineering Project SeminarⅠA Master's Course
2017 Systems Engineering SeminarⅡB Master's Course
2017 Systems Engineering SeminarⅡA Master's Course
2017 Systems Engineering SeminarⅠB Master's Course
2017 Systems Engineering SeminarⅠA Master's Course
2017 AI-based Robotics Master's Course
2016 Information and Communications Technology for Civilized Society Master's Course
2016 Systems Engineering Global Seminar Ⅰ Doctoral Course
2016 Systems Engineering Global Seminar Ⅰ Doctoral Course
2016 Systems Engineering Advanced Research Doctoral Course
2016 Systems Engineering Advanced Research Doctoral Course
2016 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2016 Systems Engineering Advanced Seminar Ⅰ Doctoral Course
2016 Systems Engineering Project SeminarⅡB Master's Course
2016 Systems Engineering Project SeminarⅡA Master's Course
2016 Systems Engineering Project SeminarⅠB Master's Course
2016 Systems Engineering Project SeminarⅠA Master's Course
2016 Systems Engineering SeminarⅡB Master's Course
2016 Systems Engineering SeminarⅡA Master's Course
2016 Systems Engineering SeminarⅠB Master's Course
2016 Systems Engineering SeminarⅠA Master's Course
2016 AI-based Robotics Master's Course
2015 AI-based Robotics
2015 Systems Engineering Advanced Seminar Ⅱ
2015 Systems Engineering Advanced Seminar Ⅰ
2015 Systems Engineering Advanced Research
2015 Systems Engineering SeminarⅡA
2015 Systems Engineering SeminarⅠA
2015 Systems Engineering Project SeminarⅡA
2015 Systems Engineering Project SeminarⅠA
2015 Systems Engineering Global Seminar Ⅰ
2015 Systems Engineering Advanced Seminar Ⅱ
2015 Systems Engineering Advanced Seminar Ⅰ
2015 Systems Engineering Advanced Research
2015 Systems Engineering SeminarⅡB
2015 Systems Engineering SeminarⅠB
2015 Systems Engineering Project SeminarⅡB
2015 Systems Engineering Project SeminarⅠB
2015 Systems Engineering Global Seminar Ⅰ
2014 Systems Engineering Advanced Research
2014 Systems Engineering Advanced Research
2014 Systems Engineering Advanced Seminar Ⅱ
2014 Systems Engineering Advanced Seminar Ⅱ
2014 Systems Engineering Advanced Seminar Ⅰ
2014 Systems Engineering Advanced Seminar Ⅰ
2014 Systems Engineering Project SeminarⅡB
2014 Systems Engineering Project SeminarⅡA
2014 Systems Engineering Project SeminarⅠB
2014 Systems Engineering Project SeminarⅠA
2014 Systems Engineering SeminarⅡB
2014 Systems Engineering SeminarⅡA
2014 Systems Engineering SeminarⅠB
2014 Systems Engineering SeminarⅠA
2014 AI-based Robotics
2014 Systems Engineering Project SeminarⅡA
2014 Systems Engineering Project SeminarⅠA
2014 Systems Engineering SeminarⅡA
2014 Systems Engineering SeminarⅠA
2014 AI-based Robotics
2013 Systems Engineering Advanced Research
2013 Systems Engineering Advanced Research
2013 Systems Engineering Advanced Seminar Ⅱ
2013 Systems Engineering Advanced Seminar Ⅱ
2013 Systems Engineering Advanced Seminar Ⅰ
2013 Systems Engineering Advanced Seminar Ⅰ
2013 Systems Engineering Project SeminarⅡB
2013 Systems Engineering Project SeminarⅡA
2013 Systems Engineering Project SeminarⅠB
2013 Systems Engineering Project SeminarⅠA
2013 Systems Engineering SeminarⅡB
2013 Systems Engineering SeminarⅡA
2013 Systems Engineering SeminarⅠB
2013 Systems Engineering SeminarⅠA
2013 AI-based Robotics
2012 AI-based Robotics
2012 Systems Engineering Advanced Seminar Ⅱ
2012 Systems Engineering Advanced Seminar Ⅰ
2012 Systems Engineering Advanced Research
2012 Systems Engineering SeminarⅡA
2012 Systems Engineering SeminarⅠA
2012 Systems Engineering Project SeminarⅡA
2012 Systems Engineering Project SeminarⅠA
2012 Systems Engineering Advanced Seminar Ⅱ
2012 Systems Engineering Advanced Seminar Ⅰ
2012 Systems Engineering Advanced Research
2012 Systems Engineering SeminarⅡB
2012 Systems Engineering SeminarⅠB
2012 Systems Engineering Project SeminarⅡB
2012 Systems Engineering Project SeminarⅠB
2011 Systems Engineering Project SeminarⅡB
2011 Systems Engineering Project SeminarⅡA
2011 Systems Engineering Project SeminarⅠB
2011 Systems Engineering Project SeminarⅠA
2011 Systems Engineering Advanced Research
2011 Systems Engineering Advanced Research
2011 NA
2011 NA
2011 Systems Engineering Advanced Seminar Ⅱ
2011 Systems Engineering Advanced Seminar Ⅱ
2011 Systems Engineering Advanced Seminar Ⅰ
2011 Systems Engineering Advanced Seminar Ⅰ
2011 AI-based Robotics
2011 AI-based Robotics Master's Course
2011 NA Master's Course
2011 NA Master's Course
2011 NA Master's Course
2011 NA Master's Course
2010 NA Master's Course
2010 NA Master's Course
2010 NA Master's Course
2010 NA Master's Course
2010 AI-based Robotics Master's Course
2009 AI-based Robotics Master's Course
2009 NA Master's Course
2009 NA Master's Course
2009 NA Master's Course
2009 NA Master's Course
2008 AI-based Robotics Master's Course
2008 NA Master's Course
2008 NA Master's Course
2008 NA Master's Course
2008 NA Master's Course
2007 AI-based Robotics Master's Course
2007 NA Master's Course
2007 NA Master's Course
2007 NA Master's Course
2007 NA Master's Course

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Satellite Courses

2016 Information and Communications Technology for Civilized Society

Research Interests

自動運転技能の学習
Lidarデータの補完
非線形回帰木
非接触インターフェース
知能ロボット
オンライン学習機能
視覚情報処理システム
多次元情報圧縮
PaLM-Tree
全方位ビジョン
視線認識
ロボット学習
ロボット学習法
ビジョン学習
線形回帰木
適応型視覚処理システム
データマイニング
主成分木
視覚移動ロボット
2DLidarデータによる自己位置推定

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Published Papers

ヴァイオリン演奏動画と楽譜を用いた演奏記号自動記入システムの開発

谷田実桜, 中村恭之（Part： Corresponding author )

計測自動制御学会論文集 60 ( 5 ) 2024.05 [Refereed]
U型Transformer構造の生成器を持つGANによる夜間雨滴画像からの雨滴除去手法と学習用夜間雨滴画像の生成法の提案

田中良弥, 中村恭之（Part： Last author )

自動車技術会論文集 55 ( 1 ) 172 - 179 2024.01 [Refereed]
周辺環境の 3 次元点群データ補間のための U-Net 型生成器をもつ敵対的生成ネットワークと補間結果評価のための指標の提案

和田拓真, 中村恭之（Part： Last author )

計測自動制御学会論文集 59 ( 12 ) 496 - 504 2023.12 [Refereed]
LaserVAE for Feature Description and an Application of Global Self-localization

WAKITA Shohei, NAKAMURA Takayuki, HACHIYA Hirotaka

Transactions of the Society of Instrument and Control Engineers ( The Society of Instrument and Control Engineers ) Vol. 55,No. 7 ( 7 ) pp.476-483 - 483 2019.07 [Refereed]

　View Summary

For accurate global self-localization, researches for the feature description of the laser-scan data have been actively conducted. Main approaches to the feature description are to design feature descriptor based on human knowledge regarding the specific environment, e.g., office and hallway. However, in real robot navigation tasks such as a security patrol robot, the robot would be applied to a variety of environments and it is expensive if the users need to tune the design at every environment. To alleviate such problem, we propose to extend the state-of-the-art variational auto-encoder (VAE) by introducing the step-edge detector, which detects non-continuous transition emerged frequently at the laser scan data due to the limitation of distance measurement. With our proposed method, called “LaserVAE”, the feature descriptor of the laser scan is automatically tuned given unknown environments. Through experiments with a real self-localization with a 2D laser scanner, we demonstrate the effectiveness of the proposed method.

DOI
選択的統合処理に基づくCIFベース大域的自己位置推定

Wakita Shohei, Nakamura Takayuki

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) Vol. 36,No. 6 ( 6 ) pp.41-50 - 428 2018.07 [Refereed]

　View Summary

This paper proposes a selective merging method of 2D range scans for enhancing our CIF-based scan matching algorithm which is a global scan matching algorithm using the CIF descriptors and a geometric constraint between keypoints. The selective merging method can generate a local map based on “terrain complexity” without fixing the number of scans to use. Our enhanced version of the CIF-based scan matching algorithm can perform global scan matching more robustly in a large cluttered environments without using an initial alignment. Through experiment in real environment, we confirm the validity of our method.

DOI
3D Faster R-CNNとレーザースキャンとの組み合わせによる特定物体の頑健な距離推定

八谷大岳,射手矢和真,中村恭之

計測自動制御学会論文集 Vol. 55,No. 1, pp.42--50 2018.01 [Refereed]
Distance estimation with 2.5D anchors and its application to robot navigation

Hirotaka Hachiya, Yuki Saito, Kazuma Iteya, Masaya Nomura and Takayuki Nakamura

ROBOMECH Journal Vol. 5,No. 1 pp.1--6 2018.01 [Refereed]
人の操作を規範としたテザー係留型飛行ロボットの制御方策の獲得

轟千明,高橋泰岳,中村恭之

知能と情報（日本知能情報ファジィ学会誌） Vol.27, No.6 pp.864-876 2015.12 [Refereed]
Acquisition of human operation characteristics for kite-based tethered flying robot using human operation data

Chiaki Todoroki, Yasutake Takahashi, Takayuki Nakamura

IEEE International Conference on Fuzzy Systems ( Institute of Electrical and Electronics Engineers Inc. ) 2015- 2015.11 [Refereed]

　View Summary

This paper shows human skill acquisition systems to control the kite-based tethered flying robot. The kite-based tethered flying robot has been proposed as a flying observation system with long-term activity capability[1]. It is a relatively new system and aimed to complement other information gathering systems using a balloon or an air vehicle. This paper shows some approaches of human operation characteristics acquisition based on fuzzy learning controller, k-nearest neighbor algorithm, and artificial neural network for the kite-based tethered flying robot using human operation data and their validity through computational simulation which we developed[2].

DOI
合同変換に不変な特徴量(CIF)とキーポイント間の幾何学的拘束に基づいたロバストなスキャンマッチング法の提案

NAKAMURA Takayuki, WAKITA Shohei

計測自動制御学会論文集 ( The Society of Instrument and Control Engineers ) Vol. 51 No. 5 ( 5 ) 309 - 318 2015.05 [Refereed]

　View Summary

This paper proposes a new global scan matching algorithm using the CIF descriptors and a geometric constraint between keypoints. The CIF descriptor was proposed in our previous work. It is a feature decriptor that is invariant against a congruence transformation. In our previous work, our method was able to perform robust local scan matching using CIF decriptors, but was apt to fail global scan mathching where a large map is used as the reference scan. In this paper, in order to resolve this problem, we propose to use a geometric constraint between keypoints in addtion to the CIF decriptors for the global scan mathching task. Our method can perform global scan matching in a cluttered environment without using an initial alignment. Through experiment in real environment, we confirm the validity of our method by comparing the performance of our method and that of our previous method.

DOI
新しい院内転倒転落防止システムの開発

小杉真一, 池田篤俊, 小笠原司, 音田恭宏, 上田悦子, 中村恭之

奈良県西和医療センター医学雑誌 ( (地独)奈良県立病院機構奈良県西和医療センター ) 4 ( 1 ) 33 - 35 2015.03 [Refereed]

　View Summary

近年、超高齢者社会の到来とともに、入院患者の高齢化が進んでおり、院内での転倒・転落による、骨折、脳神経損傷をともなう有害事例が発生し、医療安全管理上、重要な課題の一つとなっている。当院でも、院内の医療安全委員会の指導の下、転倒転落リスクの高い患者に対して、種々の防止ツールを使用している。しかし、脱落や誤作動などの問題も多く、必ずしも満足のできる成果は得られていない。そこで我々は、体感ゲーム用に開発され、医療分野にも応用され、実用化が図られている深度センサを用い、患者のベッド上での動作をモニタリングすることにより、より正確な警告を医療者に伝えるシステムを考案したので報告する。(著者抄録)
Fuzzy Control for a Kite-Based Tethered Flying Robot

Yasutake Takahashi, Tohru Ishii, Chiaki Todoroki, Yoichiro Maeda, Takayuki Nakamura

Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.19, No.3 pp.349-358 2015.03 [Refereed]
パーティクルフィルタによるロバストな自己位置同定のための疑似ユークリッドノルムに基づく尤度計算法

中村恭之, 田下裕一

日本機械学会論文集 Vol. 80, No. 816 DR0242 2014.08 [Refereed]
模倣による識別器の高速化

太田貴大,和田俊和,中村恭之

電子情報通信学会論文誌D Vol. J94-D, No.7 pp.1071-1078 2011.07 [Refereed]
Kicking motion imitation of inverted-pendulum mobile robot and development of body mapping from human demonstrator

Sataya Takahashi, Yasutake Takahashi, Yoichiro Maeda, Takayuki Nakamura

Journal of Advanced Computational Intelligence and Intelligent Informatics ( Fuji Technology Press ) 15 ( 8 ) 1030 - 1038 2011 [Refereed]

　View Summary

This paper proposes a new method for learning the dynamic motion of an inverted-pendulum mobile robot from the observation of a human player's demonstration. First, an inverted-pendulum mobile robot with upper and lower body links observes the human demonstration with a camera and extracts the human region in images. Second, the robot maps the region to its own two links and estimates link posture trajectories. The robot starts learning kicking based on the trajectory parameters for imitation. Through this process, our robot can learn dynamic kicking shown by a human. The mapping parameter gives an important role for successive imitation. A reasonable and feasible procedure of learning from observation for an inverted-pendulum robot is proposed. Learning performance from observation is investigated, then, the development of body mapping is proposed and investigated.

DOI
制約条件付き最小2乗法に基づく高速な局所型スキャンマッチング法

中村恭之

日本ロボット学会誌 ( The Robotics Society of Japan ) Vol.28,No.5 ( 5 ) pp.648-657 - 657 2010.06 [Refereed]

　View Summary

This paper describes a local scan matching method that can estimate displacements of position and orientation between two successive scans fast, accurately and robustly. To estimate displacements of position and orientation, the conventional methods need to utilize nonlinear optimization method such as Levenberg-Marquardt method since there is no closed-form solution available which minimizes an evaluation function. Due to such nonlinear optimization method, the conventional method is so time consuming. In this paper, we formulate estimating displacements of position and orientation as a constrained least square problem and provide a closed-form solution which minimizes the evalution function defined by point-to-plane error metric. In the formulation, we show that a quartic function of Lagrange multiplier can be approximated by a linear function. These formulation enables our local scan matching method to be faster than the conventional method. The experimental results in three kinds of real office environment show the usefulness of our method.

DOI
High Performance Active Camera Head Control Using PaLM-Tree

T.Nakamura, Y.Sakata, T.Wada and H. Wu

Journal of Robotics and Mechatoronics 21 pp.720-725 2009.10 [Refereed]
非線形写像学習のためのPaLM-treeの提案

中村恭之,加藤丈和,和田俊和

日本ロボット学会誌 732-742 2005.06 [Refereed]
視覚を有するエージェントのための身体性に基づく内部表現獲得手法

寺田和憲,中村恭之,武田英明,小笠原司

日本ロボット学会誌,Vol.21, No.8 65-73 2003.08 [Refereed]
全方位ビジョンセンサを搭載した移動ロボットの自己位置同定法

中村恭之,大原正満,小笠原司,石黒浩

日本ロボット学会誌 Vol.21 No.1 ( The Robotics Society of Japan ) 21 ( 1 ) 109-117 - 117 2003.01 [Refereed]

　View Summary

This paper proposes a method for estimating position and orientation of multiple robots from a set of azimuth angles of with respect to landmarks and another robots which are observed by multiple omnidirectional vision sensors. Our method simultaneously perform self-localzation by each robot and reconstruction of relative configuration between robots. Under the situation where it is impossible to identify each index for the observed azimuth angles with that for the robots, our method reconstruct not only relative configuration between robots using"triangle and enumeration constraints"but also absolute one using the knowledge of landmarks in the environment. In order to show the validity of our method, this method is applied to multiple mobile robots each of which has an omnidirectional vision sensor in the real environment. The experimental results show that the result of our method is more precise than that of self-localization by each robot.

DOI
Fast self-localization method for mobile robots using multiple omnidirectional vision sensors

T. Nakamura, M. Oohara, T. Ogasawara and H. Ishiguro, （Part： Lead author )

Machine Vision and Applications Vol.14 ( No.2 ) 129 - 138 2003 [Refereed]
Self-Partitioning State Space for Behavior Acquisition of Vision-Based Mobile Robots

Takayuki Nakamura and Tsukasa Ogasawara

Journal of Robotics and Mechatoronics, Vol.13, No.6 625-636 2001.06 [Refereed]
Embodiment based object recognition for vision-based mobile agents

Kazunori Terada, Takayuki Nakamura, Hideaki Takeda, and Tsukasa Ogasawara

Journal of Robotics and Mechatoronics, Vol.13, No.1 88-95 2001.01 [Refereed]
A cognitive robot architecture based on tactile and visual information

K.Terada, T.Nakamura, H. Takeda and T. Nishida

Advanced Robotics, 13(8) 13 ( 8 ) 767-777 - 777 2000.08 [Refereed]
オンライン学習機能を持つ視覚追跡システムの提案

中村恭之,小笠原司

日本ロボット学会誌,Vol.18 No.7 1047-1054 2000.07 [Refereed]
The RoboCup-NAIST

T Nakamura, K Terada, H Takeda, A Ebina, H Fujiwara

ROBOCUP-99: ROBOT SOCCER WORLD CUP III ( SPRINGER-VERLAG BERLIN ) 1856 727 - 730 2000 [Refereed]
A method for localization by integration of imprecise vision and a field model

K Terada, K Mochizuki, A Ueno, Takeda, I, T Nishida, T Nakamura, A Ebina, H Fujiwara

ROBOCUP-99: ROBOT SOCCER WORLD CUP III ( SPRINGER-VERLAG BERLIN ) 1856 509 - 518 2000 [Refereed]

　View Summary

In recent years, many researchers in Al and Robotics pay attention to RoboCup, because robotic soccer games needs various techniques in AI and Robotics, such as navigation, behavior generation, localization and environment recognition. Localization is one of the important issues for RoboCup. In this paper, we propose a method of robot's localization by integrating vision and modeling of the environment. The environment model that realizes the robotic soccer filed in the computer can produce in image of robot's view at any location. In the environnient model, the system can search and appropriate location of which view image is similar to the view image by the real robot. Our robot can estimate location from goal's height and aspect ratio on the camera image. We search the most suitable position with hill-climbing algorithm from the estimated location. We programmed. this method, and tested validity. The error range is reduced from 1m similar to 50cm by robot's estimation from 40cm similar to 20cm by this method. This method is superior to the other methods using dead reckoning or range sensor with map because it does not depend on the field size on precision, and does not need walls as landmark.
The RoboCup-NAIST: A cheap multisensor-based mobile robot with visual learning capability

T Nakamura, K Terada, A Shibata, H Takeda

ROBOCUP-98: ROBOT SOCCER WORLD CUP II ( SPRINGER-VERLAG BERLIN ) 1604 326 - 337 1999 [Refereed]

　View Summary

Our contribution is composed of two parts: one is development of a cheap multisensor-based mobile robot, the other is development of robust visual tracking system with visual learning capability. To promote robotic soccer research, we need a low cost and portable robot with some sensors and a communication device. This paper describes how to construct a robot system which includes a lightweight and low cost mobile robot with visual, tactile sensors, TCP/IP communication device, and portable PC where Linux is running. In real world, robust color segmentation is a tough problem because color signals are very sensitive to the slight changes of lighting conditions. In order to keep visual tracking systems with color segmentation technique running in real environment, a learning method for acquiring models for image segmentation should be developed. In this paper, we also describe a visual learning method for color image segmentation and object tracking in dynamic environment. An example of the developed soccer robot system and preliminary experimental results are also shown.
Behavior-based map representation for a sonar-based mobile robot by statistical methods

S Takamura, T Nakamura, M Asada

ADVANCED ROBOTICS ( VSP BV ) 11 ( 5 ) 445 - 462 1997

　View Summary

Many conventional methods for map generation by mobile robots have tried to reconstruct a 3D geometric representation of the environment, which is time-consuming, error-prone and necessary to transform the map into the information available for the given task. This paper proposes a method to acquire a statistical map representation robust to sensor noise and directly usable for a navigation task. The robot is equipped with a ring of ultrasonic ranging sensors and a collision avoidance behavior is embedded in it. First, the mobile robot explores the environment in order to store a set of sequences of sonar data and principle component analysis is applied to reduce the dimensionality of the sonar data. As a result, each sequence of sonar data can be described as a score pattern of principal components. Next, these patterns are classified into typical local structures of the environment in order for the robot to discriminate them. Finally, a graph representation of the environment is constructed in which the nodes and arcs correspond to these local structures and the transition probabilities between them, respectively. The validity of the method is shown by computer simulations and real robot experiments.
Stereo Sketch: Behavior Acquisition for a Stereo Vision-Based Mobile Robot

NAKAMURA Takayuki, ASADA Minoru

JRSJ ( The Robotics Society of Japan ) 15(4):533-541 ( 4 ) 533 - 541 1997

　View Summary

We have proposedmotion sketch [1] as a method to represent an interaction between a one-eyed learning agent (a mobile robot) and its environment. In this paper, we extend the basic idea inmotion sketch, tight coupling of perception and action, tostereo sketchby which a stereo-vision based mobile robot learns various kinds of behaviors such as target reaching and obstacle avoidance. Here, we deal with target reaching behavior with whichmotion sketchcopes by detecting and avoiding occlusions. First, an input scene is segmented into homogeneous regions by the enhanced ISODATA algorithm with MDL principle in terms of image coordinates and disparity information obtained from the fast stereo matcher based on the coarse-to-fine control method. Then, the segmented regions including the target area and their occlusion status identified during the stereo and motion disparity estimation process construct a state space for a reinforcement learning method to obtain a target reaching behavior. As a result of learning, the robot can avoid obstacles without describing them explicitly. We give the computer simulation results and the real robot implementation to show the validity ofstereo sketch.

DOI
Behavior-based map representation for a sonar-based mobile robot by statistical methods

T Nakamura, S Takamura, M Asada

IROS 96 - PROCEEDINGS OF THE 1996 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS - ROBOTIC INTELLIGENCE INTERACTING WITH DYNAMIC WORLDS, VOLS 1-3 ( I E E E ) 276 - 283 1996 [Refereed]

　View Summary

Many conventional methods for map generation by mobile robots have tried to reconstruct 3-D geometric representation of the environment which are time-consuming, error-prone and necessary to transform the map into the information available for the given task. This paper proposes a method to acquire a statistical map representation, robust to sensor noise and directly usable for navigation task. The robot is equipped with a ring of ultrasonic ranging sensors and a collision, avoidance behavior is embedded in it. First, the mobile robed explores in the environment in order to store a set of sequences of sonar data and the principle component analysis is applied to reduce the dimensionality of the sonar data. As a result, each sequence of sonar data cast be described as a score pattern of principal components. Next, these patterns are classified into typical local structures of the environment in order for the robot to discriminate them. Finally, a graph representation of the environment is constructed in which nodes and arcs correspond to these local structures and the transition probabilities between them, respectively. The validity of the method is shown by computer simulations and real robot experiments.
運動スケッチ：画像運動情報に基づく単眼視移動ロボットの行動獲得

人工知能学会誌 11(6):905-915 1996
Recovery of an SHGC's Shape and Pose from Shading and Contour Based on Weak Lambertian Assumption

Nakamura Takayuki, Asada Minoru, Shirai Yoshiaki

The transactions of the Institute of Electronics, Information and Communication Engineers ( The Institute of Electronics, Information and Communication Engineers ) 77 ( 7 ) 1226 - 1235 1994.07

　View Summary

本論文では,弱一様乱反射仮定に基づく定性的な拘束を用いた,一般化円筒の姿勢と形状の定量的な復元手法について述べる.弱一様乱反射仮定は,厳密な完全乱反射モデルを一般化させたもので,本手法では,光源や表面反射係数に関する知識を必要としない,まずはじめに,一般化円筒の軸の画像上での位置を求める.次に,一般化円筒表面上の掃引関数の極大点に相当する緯線上の明度分布に弱一様乱反射仮定を適用と,一般化円筒の姿勢を復元する.最後に,他の緯線上の明度分布にも,弱一様乱反射仮定を適用することにより,一般化円筒の軸の3次元空間内での位置を求める.本手法の有効性を示すために,合成画像と実画像に対する実験結果を示す.
Weak Lambertian Assumption for Determining Cylindrical Shape and Pose from Shading and Contour

Nakamura Takayuki, Asada Minoru, Shirai Yoshiaki

The transactions of the Institute of Electronics, Information and Communication Engineers ( The Institute of Electronics, Information and Communication Engineers ) 76 ( 8 ) 1637 - 1646 1993.08

　View Summary

従来の濃淡画像からの3次元形状復元(shape from shading)では,物体の表面属性が完全一様乱反射面であると仮定しているものが多い.しかしながら,実シーンにおいては,周囲光の影響やカメラ特性などにより,必ずしもこの条件を満たさない.本論文では,これらの影響を受けない弱一様乱反射仮定を導入し,照明条件(光源方向と光源強度)や表面反射係数に関する知識なしに筒状物体の形状および姿勢を復元する手法を提案する.まず実際の光源方向を,正規化光源方向と呼ぶ方向に変換する.次に,弱一様乱反射仮定に基づいて画像上の輪郭線と垂直断面形状との間に存在する変換パラメータに関する拘束式を正規化光源方向を用いて導き,この拘束式を解いて形状を復元する.更に,複数の筒状物体が入力画像中に存在する場合には,実際の光源方向を推定する.この推定された光源方向をもとに,それらの複数物体の相対的配置を推定する.合成画像と実画像を用いて本手法の有効性を示す.
Cylindrical Shape from Contour and Shading without Knowledge of Lighting Conditions or Surface Albedo

Asada Minoru, Nakamura Takayuki

Transactions of Information Processing Society of Japan ( Information Processing Society of Japan (IPSJ) ) 34 ( 5 ) 884 - 891 1993.05

　View Summary

This paper presents and algorithm for reconstructiong the shape of a cylindrical object from contour and shading without knowing the surface albedo of the object of the lighting conditions of the scene. Input image is segmented into spherical, cylindrical, or planar surfaces by analyzing local shading. The cylindrical surface is characterized with a direction of generationg lines determined from spatial derivatives in the image. The brightest generating line has strong constraints on both the shading analysis on the cylindrical surface and a simplification of the equation which represents t...
Fractal Property of Interfacial or Surface Inhomogeneous Deformation

Yoji Shibutani, Hiroshi Kitagawa, Takayuki Nakamura

Journal of the Society of Materials Science, Japan ( The Society of Materials Science, Japan ) 41 ( 470 ) 1611 - 1615 1992

　View Summary

Fractal concepts have recently been introduced to the field of fractography in order to characterize the fractured surface quantitatively. This paper puts great emphasis on the self-similarity of inhomogeneous deformation which results from the finite geometric changes of microstructure with strain. Fractal dimensions are obtained by using the familiar Richardson&amp
s structured walk method. Correspondence of the fractal property to the formation of crystallographic microstructure is discussed. We also perform fractal analyses for the pseudo-roughening profiles generated by computer simulations to interpret qualitatively the results obtained from the profiles of roughening in aluminum foils subjected to biaxial tension. Two kinds of roughening profiles are given by pure aluminum and aluminum alloy foils subjected to biaxial tension. The paper submitted formerly reported that the inhomogeneous deformation formed by the superposition of two kinds of microstructural changes was observed on pure aluminum. Fractal analyses to such profiles gave the following conclusions. The fractal dimension for pure aluminum increases a little with strain. On the other hand, as for the aluminum alloy it holds almost constant. The difference between them may be dependent on the mechanism of the formation of these roughening. This tendency also has good qualitative agreement with the results from the computer simulations by using the Gaussian distribution. Roughening formed by two kinds of the microstructural changes gives two different fractal dimensions, corresponding to the characteristic length of them. © 1992, The Society of Materials Science, Japan. All rights reserved.

DOI
Mechanism on Growth of Interfacial Roughening in Laminated Material

Yoji Shibutani, Hiroshi Kitagawa, Takayuki Nakamura

Journal of the Society of Materials Science, Japan ( The Society of Materials Science, Japan ) 41 ( 466 ) 1108 - 1113 1992

　View Summary

Inhomogeneous deformation occurring at the interface of a laminated thin sheet is considered to be one of the mechanical behaviors causing interface fracture or determining its forming limit. The behavior of deformation such as interfacial roughening may also be related with the interfacial plastic instability. Experimental investigations on such deformation have been performed by using an aluminum foil laminated with a plastic film on each side and subjecting it to biaxial tension. This report puts an emphasis on the growth of interfacial roughening in comparison with the surface roughening in the aluminum foil alone subjected to the same tension. The relation between the growth of roughening and macroscopic fracture is also discussed. Two kinds of aluminum foils were supplied, one being pure aluminum with a certain grain size and the other aluminum alloy. The interfacial roughening was observed in-situ through an optical microscope and was measured at several strain levels from the cross sections of the laminate samples which were molded by resin. It was found that the interfacial roughening did not grow monotonically due to the hardening properties and the rigidity (thickness) of the skin material. It is also regarded as one of the characteristic features of fracture that the necking occurs in the aluminum foil after the delamination at the interface propagates up to a certain region. © 1992, The Society of Materials Science, Japan. All rights reserved.

DOI

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Books etc

OpenCVによる画像処理入門改訂第3版

小枝, 正直, 上田, 悦子, 中村, 恭之( Part： Joint author, Work：第1,3,5,6,9,11章)

講談社サイエンティフィク 2022.12 ISBN: 9784065301173
これからのロボットプログラミング入門第2版 Pythonで動かすMINDSTORMS EV3 (KS情報科学専門書)

上田悦子, 小枝正直, 中村恭之

講談社 2022.03 ISBN: 4065278198
これからのロボットプログラミング入門 Pythonで動かすMINDSTORMS EV3

上田悦子, 小枝正直, 中村恭之

講談社サイエンティフィク 2020.02
OpenCVによるコンピュータビジョン・機械学習入門

中村恭之・小枝正直・上田悦子( Part： Joint author, Work：第0,10～20章，その他)

講談社サイエンティフィク 2017.08
OpenCVによる画像処理入門改訂第2版

上田悦子・小枝正直・中村恭之( Part： Joint author, Work：第1,3,5,6,9,11章，その他)

講談社サイエンティフィク 2017.07
OpenCVによる画像処理入門

上田悦子・小枝正直・中村恭之( Part： Joint author, Work：第2章,第4章,第9章，その他)

講談社サイエンティフィク 2014.07
ロボカップサッカー:中型ロボットの基礎技術 -対戦のための協調行動に向けて-

中村恭之・高橋泰岳( Part： Joint author, Work：第2.2～2.5節,第4章,第5.2節)

共立出版 2005.12
新版ロボット工学ハンドブック

日本ロボット学会( Part： Joint author, Work： 5.6節各種シミュレーションツール担当)

コロナ社 2005.05

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Misc

U-Net型生成器を持つ敵対的生成ネットワークを用いた周辺環境の3次元点群データ補完法

和田拓真, 中村恭之（Part： Corresponding author )

第28回ロボティクスシンポジア論文集 1A3 2023.03 [Refereed]
音響・画像情報を用いたヴァイオリン運弓動作と楽譜の同時認識による演奏記号自動記入システムの構築

谷田実桜, 中村恭之（Part： Corresponding author )

研究報告音楽情報科学（MUS） 2022-MUS-134 ( 27 ) 1 - 5 2022.06
バイオリン運弓動作と楽譜の同時認識による演奏記号自動記入システムの構築

谷田実桜, 中村恭之（Part： Corresponding author )

第22回計測自動制御学会システムインテグレーション部門講演会 2F3-05 2021.12
2D LiDAR データの補完機能付き VAE を用いた移動ロボットの自己位置同定手法

福田健太郎, 中村恭之（Part： Corresponding author )

ロボティクス・メカトロニクス講演会 2021 1P1-L08 2021.06
Athlete 3D pose estimation from a monocular TV sports video using pre-trained temporal convolutional networks

Tomoka Murakami, Takayuki Nakamura （Part： Corresponding author )

2020 IEEE International Conference on Systems, Man, and Cybernetics 2615 - 2620 2020.10 [Refereed]
学習済み深層ニューラルネットワークを用いたスポーツ映像における単一人物の三次元姿勢推定

村上朋郁, 中村恭之（Part： Corresponding author )

第23回画像の認識・理解シンポジウム IS1-1-16 2020.08 [Refereed]
Extraction of the graceful feature from classical dance motion focused on dancer's perspective,

Yuki Inazu, Etsuko Ueda, Kentaro Takemura, Masanao Koeda Takayuki Nakamura, et al.,

Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Body and Motion. HCII 2019, Lecture Notes in Computer Science ( Springer ) Vol. 11581 170 - 181 2019 [Refereed]

DOI
古典舞踊動作が作る曲面形状の「複雑さ」が印象評価に及ぼす影響

畠中亮太,上田悦子,竹村憲太郎,小枝正直,飯田賢一,中村恭之

第19回計測自動制御学会システムインテグレーション部門講演会(SI2018) ( 計測自動制御学会 ) 19th 1D2-02 2018.12
オートエンコーダを用いた環境地図の特徴表現と自己位置推定

脇田翔平,中村恭之,八谷大岳

ロボティクス・メカトロニクス講演会2018 ( 日本機械学会 ) 1P1-G06 2018.05
深度センサを用いた転倒転落防止システムの試用調査

中原千里, 米崎麻純, 窪田大輝, 小杉真一, 川手健次, 寺西朋裕, 武内亜紀子, 松井満政, 池田篤俊, 上田悦子, 中村恭之

奈良県西和医療センター医学雑誌 ( (地独)奈良県立病院機構奈良県西和医療センター ) 7 ( 1 ) 43 - 45 2018.03

　View Summary

人間は、加齢とともに筋力低下や歩行障害、視力の衰えなどの様々な要因が重なりバランス保持能力が低下し、転倒の危険性が高くなる。入院患者の多くは高齢者であり、転倒リスクが高くなっているのが現状である。転倒は寝たきりに繋がる重大な事故であるため、転倒予防に努めることが重要である。その中で当センタースタッフと工学研究者との共同開発により、深度センサを用いた転倒・転落防止システムを考案した。今回、実際に転倒・転落の危険がある患者に対して深度センサを使用した。そして、既存ツールの精度や深度センサの感度について調査した。これらの結果に考察を加えて報告する。(著者抄録)
自由領域制限による経路教示と経路計画のハイブリッド自律走行

野村雅也,中村恭之,八谷大岳

第23回ロボティクスシンポジア ( 日本ロボット学会 ) 2018.03 [Refereed]
3Dアンカーによる距離推定とロボットナビゲーションへの応用

八谷大岳,斎藤侑輝,射手矢和真,野村雅也,中村恭之

第23回ロボティクスシンポジア ( 日本ロボット学会 ) 2018.03 [Refereed]
2.5D Faster R-CNN for Distance Estimation.

Hirotaka Hachiya, Yuki Saito, Kazuma Iteya, Masaya Nomura, Takayuki Nakamura

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ( IEEE ) 3999 - 4004 2018 [Refereed]

DOI
Laser Variational Autoencoder for Map Construction and Self-Localization.

Shohei Wakita, Takayuki Nakamura, Hirotaka Hachiya

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ( IEEE ) 3993 - 3998 2018 [Refereed]

DOI
透視投影アンカーを用いた特定物体の検出および距離推定

八谷大岳,斎藤侑輝,射手矢和真,中村恭之

第18回システムインテグレーション部門講演集（SI2017） ( 計測自動制御学会 ) pp.1952--1954 2017.12
古典舞踊動作の腕軌道が作る曲面形状に着目した優美さ特徴抽出

畠中亮太,上田悦子,飯田賢一,竹村憲太郎,小枝正直,中村恭之

第18回システムインテグレーション部門講演集 ( 計測自動制御学会 ) 18th 2B3-05 2017.12
ディープラーニングによる特定人物検出と距離推定

八谷大岳、野村雅也、脇田翔平、射手矢和真、中村恭之

つくばチャレンジ2017参加レポート集 ( つくばチャレンジ2017 ) p.156 2017.11
経路教示と経路計画のハイブリッド自律走行

八谷大岳、野村雅也、脇田翔平、射手矢和真、中村恭之

つくばチャレンジ2017参加レポート集 ( つくばチャレンジ2017 ) p.155 2017.11
優美さ定量化のための古典舞踊動作における腕軌道と手先動作解析

畠中亮太,上田悦子,飯田賢一,竹村憲太郎,小枝正直,中村恭之

ロボティクス・メカトロニクス講演会2017 ( 日本機械学会 ) 2017 1P2-L01 - L01 2017.05

　View Summary

The purpose of this study is to propose the quantification method of grace from the classical dance motion. William Hogarth said that human motion trajectory which includes "the line of beauty" seems graceful. We are trying to establish a new method to extract "the line of beauty" features from the curved surface formed by arm movements and to quantify the grace features. This paper describes a motion feature extraction method using Gauss map from curved surfaces formed by arm movements. We also discuss the influence of the degree of freedom of the wrist on the impression of the audience.

DOI
頭部生体信号に基づく２つのニューラルネットワークの組合せによる個人適応型表情認識

平林真和,中村恭之

第22回ロボティクスシンポジア ( 日本ロボット学会 ) 2017.03 [Refereed]
古典舞踊動作の手先軌道に着目した優美さの定量化

中村匠,飯田賢一,竹村憲太郎,小枝正直,中村恭之,上田悦子

第17回計測自動制御学会システムインテグレーション部門講演会 (SI2016) ( 計測自動制御学会 ) 17th 2N2-2 2016.12
深度センサを用いた転倒転落防止システムの実態調査

中原千里,飯田めぐみ,米崎麻純,小杉真一,池田篤俊,上田悦子,中村恭之

医療の質・安全学会誌, 11 号 232 2016.11
観客視点を考慮した古典舞踊動作における手先軌道の解析

中村匠,飯田賢一,竹村憲太郎,小枝正直,中村恭之,上田悦子

ロボティクス・メカトロニクス講演会2016 ( 日本機械学会 ) 2016 ( 0 ) 2P1-12a4 - 12a4 2016.06

　View Summary

As robots in the welfare and service industries must come into contact with humans, they are required to make favorable impressions on human sensibilities. Our research focuses on the concept of "graceful motion," as defined by William Hogarth, who was an English painter and an aesthetician. To quantify the gracefulness of human motion, we approximate hand trajectories of five classical dancers by the B-spline curve. Then, we extract the S-shaped curves from these approximated trajectories and analyze its curve shape on the plane considering the audience's viewpoint. Finally, the relationship between the result of analysis and the impression evaluation is discussed.

DOI
Parametric t-SNEを利用した頭部生体信号に基づく個人適応型表情認識法の提案

平林真和,中村恭之

ロボティクス・メカトロニクス講演会2016 ( 日本機械学会 ) 1A2-11b4 2016.05
EMG信号とロボットハンド操作のダイレクトマッピング

Schleiss Michael,中村恭之

ロボティクス・メカトロニクス講演会2016 ( 日本機械学会 ) 2P1-11b3 2016.05
スキャンデータの順序保存統合と統合処理判断機能を持つ CIFベーススキャンマッチング法

脇田翔平,中村恭之

第21回ロボティクスシンポジア ( 日本ロボット学会 ) 21st 2016.03 [Refereed]
Identification of gracefulness feature parameters for hand-over motion

Etsuko Ueda, Kenichi Iida, Kentaro Takemura, Takayuki Nakamura, Masanao Koeda

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Springer Verlag ) 9732 115 - 124 2016 [Refereed]

　View Summary

As robots in the welfare and service industries must come into contact with humans, they are required to make favorable impressions on human sensibilities. Our research focuses on the concept of “graceful motion,” as defined by Hogarth. In order to implement graceful motion in robots, we analyze the hand trajectories which highly skilled servers generate in the task of passing a wine glass to extract graceful and ungraceful curve features. We propose to model the hand trajectory by a polynomial of the fourth degree and to adjust the S-shaped curvature of the hand trajectory. An impression evaluation is then conducted, which indicates that a 20% − 60% S-shaped curvature correspond to gracefulness in a hand-over motion
this parameter corresponds to Hogarth’s definition.

DOI
アジア古典舞踊動作における表現の差異

上田悦子,中村恭之,飯田賢一,小枝正直,竹村憲太郎

第16回計測自動制御学会システムインテグレーション部門講演会 (SI2015) ( 計測自動制御学会 ) 16th 1120 - 1121 2015.12
アジア古典舞踊動作における表現の差異

上田悦子,中村恭之,飯田賢一,小枝正直,竹村憲太郎

第16回計測自動制御学会システムインテグレーション部門講演会 (SI2015) ( 計測自動制御学会 ) 16th pp.1120-1121 2015.12
標本データの増加を抑制する重み付きk近傍法に基づく人の操作を規範としたテザー係留型飛行ロボットの制御

轟千明,高橋泰岳,中村恭之

第33回日本ロボット学会学術講演会 ( 日本ロボット学会 ) 1B1-03 2015.09
テザー係留型飛行ロボットのための大型地上制御ユニットの開発

轟千明, 高橋泰岳, 岡本明, 加藤万寿夫, 山崎敏夫, 田中史朗, 濱上雄大, 中村恭之

ロボティクス・メカトロニクス講演会2015 ( 日本機械学会 ) 2A1-F02 2015.05
スキャンデータの順序保存統合を用いたCIFベーススキャンマッチング法

脇田翔平,中村恭之

ロボティクス・メカトロニクス講演会2015 ( 日本機械学会 ) 2015 2A2-M09 - _2A2-M09_3 2015.05

　View Summary

This paper proposes an order-preserving merging method of 2D range scans for enhancing our CIF-based scan matching algorithm which is a global scan matching algorithm using the CIF descriptors and a geometric constraint between keypoints. Our enhanced version of the CIF-based scan matching algorithm can perform global scan matching more robustly in a large cluttered environments without using an initial alignment. Through experiment in real environment, we confirm the validity of our method.

DOI
低価格な患者見守りシステムの開発－第3報：距離画像に基づく患者状態識別法－

音田恭宏, 中村恭之,上田悦子,池田篤俊,小笠原司

第20回ロボティクスシンポジア ( 日本ロボット学会 ) pp.235--242 2015.03 [Refereed]
2A2-U05 Development of Low-cost Patient "MIMAMORT" Device : Classification of patient's state based on a depth image using a deep neural network

MAEGAWA Hiroaki, Nakamura Takayuki, UEDA Etsuko, IKEDA Atsutoshi, OGASAWARA Tsukasa

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ( The Japan Society of Mechanical Engineers ) 2015 ( 0 ) _2A2 - U05_1-_2A2-U05_3 2015

　View Summary

Recently, we have proposed a low-cost and highly reliable monitoring device which is called the MIMAMORI device for a monitoring system at a medical institute. The MIMAMORI device can detect dangerous situations, such as when a patient is at risk of rolling out of bed. In this paper, we detail the patient state classification algorithm using a deep neural network of the MIMAMORI device, and verify its practical applicability with a preliminary experiment.

DOI
Acquisition of Human Operation Characteristics for Kite-based Tethered Flying Robot using Human Operation Data

Chiaki Todoroki, Yasutake Takahashi, Takayuki Nakamura

2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015) ( IEEE ) 15220 - 15526 2015 [Refereed]

　View Summary

This paper shows human skill acquisition systems to control the kite-based tethered flying robot. The kite-based tethered flying robot has been proposed as a flying observation system with long-term activity capability[1]. It is a relatively new system and aimed to complement other information gathering systems using a balloon or an air vehicle.
This paper shows some approaches of human operation characteristics acquisition based on fuzzy learning controller, k-nearest neighbor algorithm, and artificial neural network for the kite-based tethered flying robot using human operation data and their validity through computational simulation which we developed[2].
見守りシステム「MIMAMORI」の臨床応用に向けた検証

池田篤俊,小杉真一,上田悦子,中村恭之,小笠原司

第58回自動制御連合講演会(CD-ROM) 2G1‐6 2015
Learning Control based on Intention Recognition by Inverted Two-Wheeled Mobile Robot through Interactive Operation

Shinnosuke Nomura, Takuya Inoue, Yasutake Takahashi, and Takayuki Nakamura

Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS & ISIS 2014) ( IEEE ) 30 pp. 117-122 - 34 2014.12 [Refereed]

　View Summary

Recently, cooperative operation of a human and the robot through the physical interaction has been studied and developed. As one of the human supporting robots, inverted pendulum two-wheeled mobile robots have been proposed to support human transportation with/without a heavy luggage. In our laboratory, we have studied a suitcase-type two-wheeled inverted pendulum mobile robot that changes the control parameters according to the user intention. The robot recognizes the user intention by the user's physical operation of the robot. It changes the control parameter according to the recognized user intention and supports the luggage transportation. It is necessary to learn the parameters of the control and user-intention recognition user by user because the user preference is different one by one. This paper proposes a method to learn the control parameters and their corresponding intention recognition parameters of the user for a suitcase-type inverted-pendulum mobile robot for appropriate assistive control. In order to show the validity of the proposed method, it shows some experimental results with a real robot.

DOI
Low-cost and Highly Reliable MIMAMORI Device for Patient Monitoring

A. Ikeda, Y. Otoda, E. Ueda, T. Nakamura and T. Ogasawara

IEEE International Conference on Robotics and Biomimetics ( IEEE ) 1697 - 1702 2014.12 [Refereed]
Learning Fuzzy Control Parameters for Kite-based Tethered Flying Robot using Human Operation Data

Chiaki Todoroki, Yasutake Takahashi, and Takayuki Nakamura

Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS & ISIS 2014) ( IEEE ) pp.111-116 2014.12 [Refereed]
インタラクティブな操作を行う倒立二輪型ロボットのための意図認識モジュールの漸次的学習

野村慎之介,井上卓也,高橋泰岳,中村恭之

日本知能情報ファシィ学会合同シンホシウム 2014 ( 日本知能情報ファシィ学会 ) pp.3-44 2014.11
人の操作データに基づくテザー係留型飛行ロボットのためのファジィ制御パラメータの学習

轟千明,高橋泰岳,中村恭之

第32回日本ロボット学会学術講演会 ( 日本ロボット学会 ) 3J2-03 2014.09
インタラクティブな操作を行うユーザの意図認識による倒立二輪型ロボットの学習制御

野村慎之介,井上卓也,高橋泰岳,中村恭之

第30回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) 30 pp.29-34 - 34 2014.09

　View Summary

Recently, cooperative operation of a human and the robot through the physical interaction has been studied and developed. As one of the human supporting robots, inverted pendulum two-wheeled mobile robots have been proposed to support human transportation with/without a heavy luggage. In our laboratory, we have studied a suitcase-type two-wheeled inverted pendulum mobile robot that changes the control parameters according to the user intention. The robot recognizes the user intention by the user's physical operation of the robot. It changes the control parameter according to the recognized user intention and supports the luggage transportation. It is necessary to learn the parameters of the control and user-intention recognition user by user because the user preference is different one by one. This paper proposes a method to learn the control parameters and their corresponding intention recognition parameters of the user for a suitcase-type inverted-pendulum mobile robot for appropriate assistive control. In order to show the validity of the proposed method, it shows some experimental results with a real robot.

DOI
Fuzzy Control for Kite-based Tethered Flying Robot

Tohru Ishii, Yasutake Takahashi, Yoichiro Maeda and Takayuki Nakamura

IEEE International Conference on Fuzzy Systems ( IEEE ) 746 - 751 2014.07 [Refereed]
Intention Recognition by Inverted Two-Wheeled Mobile Robot through Interactive Operation

Yasutake Takahashi, Takuya Inoue and Takayuki Nakamura

IEEE International Conference on Fuzzy Systems ( IEEE ) 1291 - 1296 2014.07 [Refereed]
合同変換に不変な特徴量(CIF)とキーポイント間の幾何学的拘束に基づいたロバストなスキャンマッチング法の提案

脇田翔平,中村恭之

ロボティクスメカトロニクス講演会2014 ( 日本機械学会 ) 2014 2A2-T05 - _2A2-T05_4 2014.05

　View Summary

This paper proposes a new global scan matching algorithm using the CIF descriptors and a geometric constraint between keypoints. The CIF descriptor was proposed in our previous work. It is an feature descriptor that is invariant against a congruence transformation. Our method can perform global scan matching in a cluttered environments without using an initial alignment. Through experiment in real environment, we confirm the validity of our method.

DOI
インタラクティブな操作を行う倒立二輪型ロボットによるユーザ意図認識と制御

井上卓也,高橋泰岳,中村恭之

ロボティクスメカトロニクス講演会2014 ( 日本機械学会 ) 2A1-R01 2014.05
高品質なみかん栽培のためのセンサシステムの開発

中村恭之

ロボティクスメカトロニクス講演会2014 ( 日本機械学会 ) 1P2-W04 2014.05
RGB-D カメラを用いた3 次元物体認識のためのHS-SHOT 特徴量の提案

中村裕介,中村恭之

ロボティクスメカトロニクス講演会2014 ( 日本機械学会 ) 3P1-X05 2014.05
テザー係留型飛行ロボットの開発と自律飛行制御

石井徹,轟千明,高橋泰岳,前田陽一郎,中村恭之

ロボティクスメカトロニクス講演会2014 ( 日本機械学会 ) 2A1-A04 2014.05
2Dスキャンデータの合同変換に不変な特徴量(CIF)を用いたスキャンマッチング

中村恭之,脇田翔平

第19回ロボティクスシンポジア ( 日本ロボット学会 ) 19th 6C3, pp.592--598 2014.03 [Refereed]
力学的操作による意図認識に基づく倒立二輪型ロボットの制御

井上卓也,高橋泰岳,中村恭之

第2回人間共生システムデザインコンテスト(HSS-DC) & 第16回HSS研究会 ( 日本知能情報ファシィ学会 ) G1-2 2014.03
Robust global scan matching method using congruence transformation invariant feature descriptors and a geometric constraint between keypoints

Takayuki Nakamura, Shohei Wakita

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics ( Institute of Electrical and Electronics Engineers Inc. ) 2014- ( January ) 3103 - 3108 2014 [Refereed]

　View Summary

This paper proposes a new global scan matching algorithm using the CIF descriptors and a geometric constraint between keypoints. The CIF descriptor was proposed in our previous work. It is a feature decriptor that is invariant against a congruence transformation. In our previous work, our method was able to perform robust local scan matching using CIF decriptors, but was apt to fail global scan mathching where a large map is used as the reference scan. In this paper, in order to resolve this problem, we propose to use a geometric constraint between keypoints in addtion to the CIF decriptors for the global scan mathching task. Our method can perform global scan matching in a cluttered environment without using an initial alignment. Through experiment in real environment, we confirm the validity of our method by comparing the performance of our method and that of our previous method.

DOI
テザー係留型飛行ロボットのシミュレータ開発

轟千明,高橋泰岳,中村恭之

日本知能情報ファジィ学会第22回北信越支部シンポジウム ( 日本知能情報ファジイ学会 ) 2013.11
Tethered Flying Robot for Information Gathering System

Tohru Ishii, Yasutake Takahashi, Yoichiro Maeda and Takayuki Nakamura

IROS'13 Workshop on Robots and Sensors integration in future rescue INformation system (ROSIN'13) ( IEEE ) 2013.11 [Refereed]
インタラクティブな操作を行う倒立二輪型ロボットによる意図認識

井上卓也,高橋泰岳,中村恭之

日本知能情報ファジィ学会第22回北信越支部シンポジウム ( 日本知能情報ファジイ学会 ) 2013.11
自立支援用ロボットアームのための簡便な操作インターフェースの開発

中村恭之

日本ロボット学会学術講演会2013併設シンポジウム「介護・リハビリ・自立のための実用的なロボット技術の創出」講演集 ( 日本ロボット学会 ) pp.56-57 2013.09
車輪型移動ロボットのための直感的操作を可能とする遠隔操縦インターフェースの開発

赤阪拓也,中村恭之

情報処理学会関西支部支部大会2013 ( 情報処理学会 ) G101 2013.09
2Dスキャンデータの合同変換に不変な特徴量(CIF)を用いたロバストなスキャンマッチング

中村恭之,脇田翔平

第31回日本ロボット学会学術講演会 ( 日本ロボット学会 ) 3J1-02 2013.09
2Dスキャンデータの合同変換に不変な特徴量(CIF)を用いたロバストなスキャンマッチング

中村恭之,脇田翔平

第31回日本ロボット学会学術講演会 ( 日本ロボット学会 ) 3J1-02 2013.09
KinectとARtoolkitを用いた簡便な福祉用ロボットアーム制御システムの開発

小川洋平,中村恭之

ロボティクスメカトロニクス講演会2013 ( 日本機械学会 ) 1P1-Q01 2013.05
ロバストなスキャンマッチングのための合同変換に不変な特徴量(CIF)の提案

田下裕一,中村恭之

ロボティクスメカトロニクス講演会2013 ( 日本機械学会 ) 1A2-H10 2013.05
脳信号収集ワイヤレスヘッドセットを用いた電動車椅子ロボットの制御

茨木仁希,中村恭之

ロボティクスメカトロニクス講演会2013 ( 日本機械学会 ) 2A1-C06 2013.05
多次元データの高速・頑健なクラスタリングためのHetero-BOOLアルゴリズムの提案

安達郁視,中村恭之

第18回ロボティクスシンポジア ( 日本ロボット学会 ) 2D4, pp.251-256 2013.03 [Refereed]
教師なしクラスタリング手法による距離画像上等高線の高速生成

安達郁視,中村恭之

動的画像処理実利用ワークショップ ( 精密工学会 ) O3-2, pp.53-54 2013.03 [Refereed]
Modeling of graceful motions: Determining characteristics of graceful motions from handover motion

T. Tanaka, T. Tsuduki, E. Ueda, K. Takemura, T. Nakamura

WIT Transactions on Modelling and Simulation ( WITPress ) 55 453 - 463 2013 [Refereed]

　View Summary

Since robots in the welfare and service industries make contact with humans, they have to produce favorable impressions in the human mind. This study proposes graceful motions of humans and aims to quantify it to make robot motions more favorable. We have focused on the handover motion of a glass and selected waiters as subjects. Their motions were recorded as trajectories by motion capture system and evaluated by observers. The result revealed that the motions of them produce favorable and graceful impressions. The trajectory was projected on a two-dimensional plane surface that was obtained by conducting principal component analysis. The projected trajectory was calculated by fitting 2 spline curves. As a result, the common characteristics of graceful motions were extracted as parameters of spline curves and graceful motions are characterized by S-shaped trajectories. After that, 4 motions were created using 3DCG by changing extracted parameters step by step to verify which parameters provide graceful impressions through simulations. Finally, the parameters that produce graceful and favorable impressions were determined. © 2013 WIT Press.

DOI
Real-Time 3-D Path Generation Method for a Robot Arm by a 2-D Dipole Field

Takayuki Nakamura

2013 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM): MECHATRONICS FOR HUMAN WELLBEING ( IEEE ) 745 - 749 2013 [Refereed]

　View Summary

This paper proposes a simple algorithm for generating a 3-D path of an end effector of a robot arm in real-time. We assume that the global position and orientation of the robot's end effector, a waypoint and a destination are known. Our algorithm computes a 2-D dipole field on the local plane through the end effector, the waypoint and the destination. The robot's end effector moves along the 2-D dipole field. Through experiments in computer simulation and real environment, we confirm the validity of our method.
Congruence Transformation Invariant Feature Descriptor for Robust 2D Scan Matching

Takayuki Nakamura, Yuuichi Tashita

2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) ( IEEE ) 1648 - 1653 2013 [Refereed]

　View Summary

The ability of computing similarities between two data sets is a key for many applications such as video tracking, object recognition, image stitching, 3D modeling and so on. Recently, Lowe has discovered a promissing approach for matching 2D images based on the local invariant feature descriptor called SIFT [1]. We are really inspired by Lowe's method. In this paper, we propose a new local invariant feature descriptor for matching 2D scan data. The proposed feature descriptor is called "CIF", that is a feature which remains unchanged when a congruence transformation is applied. We can perform global scan matching in cluttered environments by matching an input scan with a reference scan based on CIF without any initial alignments. the validity of our method is confirmed by experiments in real environment.

DOI
人間動作の経由点表現を用いた倒立二輪型移動ロボットによる摸倣学習

木村竜也, 高橋泰岳, 前田陽一郎, 中村恭之

第28回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) pp.458-463 2012.09
人間動作の経由点表現を用いた倒立二輪型移動ロボットによる摸倣学習

木村竜也, 高橋泰岳, 前田陽一郎, 中村恭之

第28回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) pp.458-463 2012.09
擬似ユークリッドノルムに基づくパーティクルフィルタによる移動ロボットの自己位置同定

田下裕一,中村恭之

日本ロボット学会学術講演会2012 ( 日本ロボット学会 ) 4J1-8 2012.09
テザー係留型飛行ロボットの自律飛行制御

石井徹(福井大学大学院),高橋泰岳(福井大学大学院),前田陽一郎(福井大学大学院),中村恭之

日本ロボット学会学術講演会2012 ( 日本ロボット学会 ) 4F3-3 2012.09
PSDセンサを用いた車輪倒立振子型ロボットの制御

木村竜也(福井大学),高橋泰岳(福井大学),前田陽一郎(福井大学),中村恭之

日本ロボット学会学術講演会2012 ( 日本ロボット学会 ) 2G1-5 2012.09
人間動作の経由点表現を用いた倒立二輪型移動ロボットによる摸倣学習

木村竜也, 高橋泰岳, 前田陽一郎, 中村恭之

第28回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) pp.458-463 2012.09
KinectのRGB-Dカメラのための自動キャリブレーション法

中村裕介,中村恭之

画像の認識・理解シンポジウム2012 ( 電子情報通信学会 ) IS3-22 2012.08 [Refereed]
Kinect センサーのためのRGB-D カメラ自動キャリブレーション

中村恭之,中村裕介

ロボティクスメカトロニクス講演会2012 ( 日本機械学会 ) 1A2-A06 2012.05
ダイポール場を利用したロボットアームの実時間軌道生成法

中村恭之,中原由希子

ロボティクスメカトロニクス講演会2012 ( 日本機械学会 ) 2A1-A01 2012.05
Body mapping from human demonstrator to inverted-pendulum mobile robot for learning from observation

Yasutake Takahashi, Tatsuya Kimura, Yoichiro Maeda, Takayuki Nakamura

IEEE International Conference on Fuzzy Systems ( IEEE ) 1 - 6 2012 [Refereed]

　View Summary

This paper proposes a method for learning the kicking motion of an inverted-pendulum mobile robot from the observation of a human player's demonstration. An inverted-pendulum mobile robot with upper and lower body links observes the human demonstration with a motion capture system and estimates the posture of each human links. The robot maps the links to its own two links and estimates link posture trajectories during the kicking motion. The robot starts learning kicking based on the trajectory parameters for imitation. Through this process, our robot can learn dynamic kicking shown by a human. The mapping gives an important role for successive imitation. A reasonable and feasible procedure of learning from observation for an inverted-pendulum robot is proposed. Learning performance from observation is investigated with a preliminary experiment. © 2012 IEEE.

DOI
テザー係留型飛行ロボット

十河,石井,高橋,前田,永田,中村

第27回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) 2011.09
倒立二輪型移動ロボットによる人間の動的動作模倣のための身体部位マッピング

高橋,木村,野々下,高橋,前田,中村

第27回ファジイ・システム・シンポジウム ( 日本知能情報ファジイ学会 ) 2011.09
指示を求めるオフィスロボットの開発

田下裕一,中村恭之

平成23年度情報処理学会関西支部大会 ( 情報処理学会 ) D-102 2011.09
倒立二輪型移動ロボットによる人間の動的動作模倣のための身体部位マッピング

高橋佐多弥,高橋泰岳,前田陽一郎,中村恭之

第25回人工知能学会全国大会 ( 人工知能学会 ) 2011.05
3次元距離情報と色情報の統合に基づく3次元物体追跡

中村恭之

ロボティクスメカトロニクス講演会2011 ( 日本機械学会 ) 2A1-L07 2011.05
Person Tracking System with Active Camera

LI Peng, QI Yiqiang, WU Haiyuan, NAKAMURA Takayuki, MIURA Hirokazu, TAKI Hirokazu

電気学会研究会資料. IIS, 次世代産業システム研究会 = The papers of Technical Meeting on Innovative Industrial System, IEEE Japan 2011 ( 21 ) 23 - 26 2011.03
Detection of Grasping Position for Robot Hand Using Three-dimensional Vision without Shape Models

HIRATA Masaya, MIURA Hirokazu, NAKAMURA Takayuki, WU Haiyuan, TOMITA Fumiaki, NISHI Takao, MATSUDA Noriyuki, TAKI Hirokazu

電気学会研究会資料. IIS, 次世代産業システム研究会 = The papers of Technical Meeting on Innovative Industrial System, IEEE Japan 2011 ( 21 ) 15 - 18 2011.03
Classifier acceleration by imitation

Takahiro Ota, Toshikazu Wada, Takayuki Nakamura

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6495 ( 4 ) 653 - 664 2011 [Refereed]

　View Summary

This paper presents a framework named "Classifier Molding" that imitates arbitrary classifiers by linear regression trees so as to accelerate classification speed. This framework requires an accurate (but slow) classifier and large amount of training data. As an example of accurate classifier, we used the Compound Similarity Method (CSM) for Industrial Ink Jet Printer (IIJP) character recognition problem. The input-output relationship of trained CSM is imitated by a linear regression tree by providing a large amount of training data. For generating the training data, we developed a character pattern fluctuation method simulating the IIJP printing process. The learnt linear regression tree can be used as an accelerated classifier. Based on this classifier, we also developed Classification based Character Segmentation (CCS) method, which extracts character patterns from an image so as to maximize the total classification scores. Through extensive experiments, we confirmed that imitated classifiers are 1500 times faster than the original classifier without dropping the recognition rate and CCS method greatly corrects the segmentation errors of bottom-up segmentation method. © 2011 Springer-Verlag Berlin Heidelberg.

DOI
Development of body mapping from human demonstrator to inverted-pendulum mobile robot for imitation

Sataya Takahashi, Yasutake Takahashi, Yoichiro Maeda, Takayuki Nakamura

IEEE International Conference on Fuzzy Systems ( IEEE ) 1344 - 1349 2011 [Refereed]

　View Summary

This paper addresses development of body mapping from a human demonstrator to an inverted-pendulum mobile robot for imitation. An inverted-pendulum mobile robot with torso and body links learns a dynamic kicking motion shown by a human. The robot observes the human demonstration with a camera, extracts the human region in each of images, maps the region to its own two links, estimates the link posture trajectories, and starts kicking motion learning based on the trajectory parameters for imitation. The mapping parameter gives an important role for successive imitation. A reasonable and feasible procedure of learning from observation for an inverted-pendulum robot and development of the body mapping is proposed and investigated in this paper. © 2011 IEEE.

DOI
Real-time 3-D object tracking using Kinect sensor

Takayuki Nakamura （Part： Lead author )

2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011 ( IEEE ) 784 - 788 2011 [Refereed]

　View Summary

In this paper, we propose a novel method for real-time three-dimensional (3-D) object tracking based on integration of 3-D range and color information. To get 3D range and color information simultaneously, our method utilizes the Microsoft Kinect sensor which is composed of depth and color cameras. 3-D range and color information are integrated using the estimated depth and color cameras intrinsic parameters and relative transformation between the cameras. The target region can be tracked by processing depth pixels with color information. Through experiment in real environment, we confirm the validity of our method. © 2011 IEEE.

DOI
Inverted-Pendulum Mobile Robot Motion Learning from Human Player Observation

Sataya Takahashi, Hiroaki Nonoshita, Yasutake Takahashi, Y.Maeda, Takayuki Nakamura

Proceedings of Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems ( Japan Society for Fuzzy Theory and intelligent informatics (SOFT) ) pp.211-216 2010.12 [Refereed]
方策勾配法を用いた倒立振子型移動ロボットの蹴球動作学習

野々下博昭,高橋泰岳,中村恭之,前田陽一郎

第28回日本ロボット学会学術講演会 ( 日本ロボット学会 ) 2010.09
Behavioral Development of Ball Kicking Motion of a Two-wheeled Inverted Pendulum Mobile Robot

Yasutake Takahashi, Hiroaki Nonoshita, Takayuki Nakamura, Yoichiro Maeda

2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010) ( IEEE ) pp.830-835 2010 [Refereed]

　View Summary

In this paper, we introduce a method for generating a dynamic motion such that a two-wheeled inverted pendulum robot kicks a ball far away utilizing its own body dynamics while it keeps standing. Such a dynamic motion can be acquired through trial and error based on a reinforcement learning scheme. We utilize a simple policy gradient method to acquire a kicking motion which is designed by defining the desired parameters such as body angle, wheel angular velocity and so on. To show the validity of our approach, we perform computer simulation experiments of behavior acquisition for the two-wheeled inverted pendulum robot. Based our approach, we succeeded in acquiring the kicking motion of the two-wheeled inverted pendulum robot. A very interesting finding is: each of the acquired motions deviates from the desired trajectory, which is given by the human designer while keeping evaluation value of the acquired motion high.
2A2-D18 Learning Dynamic Throwing Motion of A Wheeled Inverted Pendulum utilizing Whole Body Dynamics

Nishikawa Takehiro, TAKAHASHI Yasutake, NAKAMURA Takayuki, ASADA Minoru, ISHIGURO Hiroshi

ロボティクス・メカトロニクス講演会講演概要集 ( The Japan Society of Mechanical Engineers ) 2009 "2A2 - D18(1)"-"2A2-D18(4)" 2009.05

　View Summary

We apply reinforcement learning to a wheeled inverted pendulum robot that acquires dynamic throwing motion utilizing whole body dynamics. Large number of parameters are needed to be calibrated so that the robot becomes able to throw a ball far away utilizing its own body dynamics while it keeps standing. We investigated the learning process of the throwing motion by application of a policy gradient method with a dynamics simulater.
2P1-F06 Picking Up By A Wheeled Inverted Pendulum Manipulator

Nakamura Takayuki

ロボティクス・メカトロニクス講演会講演概要集 ( The Japan Society of Mechanical Engineers ) 2009 "2P1 - F06(1)"-"2P1-F06(3)" 2009.05

　View Summary

In this paper, we propose a new nonlinear programming based motion generator for a wheeled inverted pendulum manipulator. Our method utilizes L-BFGS-B method which can handle inequality constraints intrinsically and whose computational cost is low. Our method can generate various motions of the robot only by setting up an objective function for a given task. Through computer simulation, we confirm the validity of our method.
2P2-C12 A Coarse-to-Fine Strategy for Fast Scan Matching

Nakamura Takayuki, Maeda Yukihiro

ロボティクス・メカトロニクス講演会講演概要集 ( The Japan Society of Mechanical Engineers ) 2008 "2P2 - C12(1)"-"2P2-C12(4)" 2008.06

　View Summary

In this paper, we propose a fast and reliable scan matching method so that it can be used in the cluttered environment. To speed up the processing time, our method utilize coarse-to-fine strategy. First, our method employs histgram matching approach to estimate displacements of position and orientation roughly. Second, to estimate them accurately, our method employ constrained least square method based on the formulation using poin-to-line metric. Such metric is also effective to the cluttered environment. The experimental results show the usefulness of our method.
2P2-H02 Generating Various Motions of Multiple Articulated Mobile Robot with Nonlinear Programming

Nakamura Takayuki

ロボティクス・メカトロニクス講演会講演概要集 ( The Japan Society of Mechanical Engineers ) 2008 "2P2 - H02(1)"-"2P2-H02(4)" 2008.06

　View Summary

In this paper, we propose a new nonlinear programming based inverse kinematics solver for generating various motions of a multiple articulated robot. Our method utilizes L-BFGS-B method which can handle inequality constraints intrinsically and whose computational cost is low. Our method can generate various motions of a multiple articulated robot only by setting up objective functions. In this paper, we provide several objective functions one of which can generate the motion of a floating-base robot and which can generate self-motion of the redundant robot without calculating the pseudoinve...
Generating Various Motions of Multiple Articulated Mobile Robot with Nonlinear Programming

The 10th International Conference on the SIMULATION OF ADAPTIVE BEHAVIOR (SAB'08) P28 2008 [Refereed]
測域センサデータの直線追跡に基づくスキャンマッチング法

武野哲也, 中村恭之, 和田俊和

画像の認識・理解シンポジウム(MIRU2007) 1564 - 1569 2007.07 [Refereed]
主成分木を用いた写像学習法の提案と性能比較

荒井英剛,中村恭之,和田俊和

MIRU2007画像の認識・理解シンポジウム論文集 pp. 516--521 2007.07
2A2-F07 Self Localization Method for Vision-based Mobile Robot Using Multiple Parallel Line Patterns

Kawano Hiroaki, Nakamura Takyuki, Yokomori Ryosuke, Chen Qian, Wada Toshikazu

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2007 "2A2 - F07(1)"-"2A2-F07(3)" 2007.05

　View Summary

We propose a new self-localization method for a mobile robot equipped with a fixed-viewpoint active camera by observing multiple parallel lines patterns with the camera. The method utilizes the technique for estimating location and posture of the camera from one parallel lines pattern which was previously developed by our research group. The method switches from a certain parallel lines pattern used for self-localization to another parallel lines pattern while the robot is moving in the environment. After the new parallel lines pattern is selected, the method keeps estimating location and p...
2P1-G05 Local Environmental Map Generation Based on Tracking Lines in Laser Range Data

Takeno Tetsuya, Nakamura Takayuki, Wada Toshikazu

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2007 "2P1 - G05(1)"-"2P1-G05(3)" 2007.05

　View Summary

We propose a new scan matching algorithm that makes use of the simple polygonal structure of environment. Our method extracts line segments from a current scan and matches them with line segments in a previous scan, that is, tracks the line segments in the sequence of scan. Our method simultaneously computes the pose shift (Δx ,Δy,Δθ) based on the correspondence between line segments in the two successive scans and the transformation such that the current scan is mapped optimally to the previous scan. By the use of line segments in the scan, it is possible to detect invariants for position ...
分離度フィルタと PaLM-treeを用いた視線方向の推定

松本拓也, 呉海元, 和田俊和, 中村恭之

画像の認識・理解シンポジウム(MIRU2006) 1042 - 1047 2006.07 [Refereed]
機械学習法のロボット知能化システムへの応用(2)

中村恭之, 和田俊和

機械の研究 ( 養賢堂 ) 58 ( 2 ) 263 - 267 2006.02
機械学習法のロボット知能化システムへの応用(1)

中村恭之, 和田俊和

機械の研究 ( 養賢堂 ) 58 ( 1 ) 7 - 16 2006.01
2A1-E08 Tightly coupled planning and model learning for real robot behavior learning

Kawahara Terumi, Nakamura Takayuki, Wada Toshikazu

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2006 "2A1 - E08(1)"-"2A1-E08(4)" 2006

　View Summary

This paper presents a new framework for learning dynamic robot behavior such that a wheeled mobile robot moves to the destination with wheel slippage. First, our method learns the body dynamics from a large number of sensory-motor instances using PaLM-tree algorithm, which approximates nonlinear mapping in arbitrary preciseness. The mapping specifies a transition model from state-action pair to next state. An optimal action sequence generating the transition from initial to goal states is obtained by the branch-and-bound algorithm using the estimated transition model. Then, new sensory-moto...
Instance Based Construction of Distinctiveness Map and Its Application : Distinctiveness Map Based Stereo Tracking

IIZUKA Takeo, WADA Toshikazu, HUA Chunsheng, NAKAMURA Takayuki

IPSJ SIG Notes. CVIM ( 一般社団法人情報処理学会 ) 2005 ( 112 ) 9 - 16 2005.11

　View Summary

This paper presents a measure for color based target detection and tracking. The measure, distinctiveness, extends our nearest neighbor classification based color target detection to target tracking. Since the color target detection can only detects target regions, if no target is detected near tracking region, the tracking fails. However, if we have a measure representing the distinctiveness of the target color, we can keep tracking by finding the regions having higher distinctiveness. The distinctiveness is defined not only by the color distance from the target color set but also by the d...
事例を用いた顕著性マップの構築とその応用

飯塚,和田,華,中村

情報処理学会研究報告2005-CVIM-151 65-70 2005.11
Learning Nonlinear Mapping based on Recursive Partitioning of Data Space : Current and Old Trend on Regression Tree

NAKAMURA Takayuki, WADA Toshikazu

Journal of Information Processing Society of Japan ( 一般社団法人情報処理学会 ) 46 ( 9 ) 1030 - 1038 2005.09
LF-006 Estimating the Number of Tracking Targets for Human Location Tracking Using Floor Pressure Sensors

Satoh Tetsu, Wada Toshikazu, Nakamura Takayuki

情報科学技術レターズ ( Forum on Information Technology ) 4 ( 4 ) 103 - 104 2005.08
High Performance Control of Active Camera Head Using PaLM-Tree

T.Nakamura, Y.Sakata, T.Wada and H. Wu

IEEE/ASME International Conference on Advanced Intelligent Mechatronics 2005 963-968 2005.08 [Refereed]

　View Summary

基本アルゴリズムの考案,実験, 検証
MDL基準に基づく区分的関数あてはめによる写像学習

上江洲吉美, 中村恭之, 和田俊和

画像の認識・理解シンポジウム(MIRU2005) 144 - 150 2005.07 [Refereed]
視点固定型パン・チルトステレオカメラによるリアルタイム3次元位置計測システム

飯塚健男, 和田俊和, 中村恭之, 加藤丈和, 吉岡悠一

画像の認識・理解シンポジウム(MIRU2005) デモセッション 1620 - 1621 2005.07 [Refereed]
識別器選択のための入力空間分割法に関する検討

林拓, 中村恭之, 和田俊和

画像の認識・理解シンポジウム(MIRU2005) 859 - 866 2005.07 [Refereed]
計画と実行の反復による車輪型移動ロボットの滑り運動学習

川原輝美, 中村恭之, 和田俊和

第10回ロボティクスシンポジア予稿集 405 - 409 2005.03 [Refereed]
MDL-based nonlinear regression tree

UEZU Yoshimi, NAKAMURA Takayuki, WADA Toshikazu

IEICE technical report. Natural language understanding and models of communication ( 社団法人電子情報通信学会 ) 104 ( 667 ) 13 - 18 2005.02

　View Summary

In the previous work, we proposed the "PaLM-Tree" which is a kind of linear regression tree. It improves some drawbacks which the conventional linear regression tree method have. When it is applied for estimating a complex nonlinear mapping, it splits the input space into too much regions. In such case, the generalization performance of the PaLM-tree tends to be worse. In order to improve the generalization performance of the PaLM-tree, we proposed a MDL-based nonlinear regression tree. Instead of using linear regression functions, this method uses polynomial functions. Furthermore, it util...
Space Partitioning Method for Classifier Selection

HAYASHI Hiromu, NAKAMURA Takayuki, WADA Toshikazu

IEICE technical report. Natural language understanding and models of communication ( 社団法人電子情報通信学会 ) 104 ( 667 ) 7 - 12 2005.02

　View Summary

Ensemble learing is a method for constructing a strong crassifier from multiple weak classifiers. In this method, the accuracy of the strong classifier is improved, however, the classification speed and memory consumption degenerate. This is because that the strong classifier requires outputs of all weak classifiers for a single input. Our approach consists of two ideas : decomposing the input space into boxes and selecting the best classifier for each box from a certain classifier set. In this approach, since a single classifier is selected for a single input, the classification speed is a...
1P2-S-067 High performance control of active camera head using PaLM-tree(Evolution and Learning for Robotics 3,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)

Sakata Yoshio, Nakamura Takayuki, Wu Haiyuan, Wada Toshikazu

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ( The Japan Society of Mechanical Engineers ) 2005 ( 0 ) 133 - 133 2005

DOI
Regression Trees and Its Application to Classification Problems

Wada Toshikazu, Nakamura Takayuki

IPSJ SIG Notes. CVIM ( 一般社団法人情報処理学会 ) 2004 ( 91 ) 203 - 210 2004.09

　View Summary

This paper presents evolutional history of regression trees, a novel regression tree called PaLM-tree, and its application to Computer Vision and Pattern Recognition problems. Regression tree is a tree representation of nonlinear function, which is mainly investigated in the fields of Machine Learning and Data Mining. The original regression tree is a simple tree representation holding function values at leaves (terminated nodes). Linear regression tree extends the function values to linear regression coefficients. Since these regression trees are designed for rule-extraction, most of them ...
Regression Trees and Its Application to Classification Problems

Wada Toshikazu, Nakamura Takayuki

Technical report of IEICE. PRMU ( 社団法人電子情報通信学会 ) 104 ( 291 ) 33 - 40 2004.09

　View Summary

This paper presents evolutional history of regression trees, a novel regression tree called PaLM-tree, and its application to Computer Vision and Pattern Recognition problems. Regression tree is a tree representation of nonlinear function, which is mainly investigated in the fields of Machine Learning and Data Mining. The original regression tree is a simple tree representation holding function values at leaves (terminated nodes). Linear regression tree extends the function values to linear regression coefficients. Since these regression trees are designed for rule-extraction, most of them ...
回帰木を用いた非線形写像の学習と識別問題への応用

和田,中村

電子情報通信学会PRMU研究会資料 ( Information Processing Society of Japan (IPSJ) ) 2004 ( 91 ) 203 - 210 2004.09 [Refereed]

　View Summary

This paper presents evolutional history of regression trees, a novel regression tree called PaLM-tree, and its application to Computer Vision and Pattern Recognition problems. Regression tree is a tree representation of nonlinear function, which is mainly investigated in the fields of Machine Learning and Data Mining. The original regression tree is a simple tree representation holding function values at leaves (terminated nodes). Linear regression tree extends the function values to linear regression coefficients. Since these regression trees are designed for rule-extraction, most of them are single valued for representing nonlinear scalar functions. PaLM-tree is a multi-valued extension of the linear regression tree with Split-and-Merge tree construction. PaLM-tree can be applied to varieties of nonlinear mapping learning problems. This paper also presents applications of PaLM-tree involving image segmentation, camera calibration and imitating classifiers.
I-067 Face Direction Estimation using Nonlinear Map Learning Algorithm "PaLM-tree"

Satoh Tetsu, Wada Toshikazu, Nakamura Takayuki

情報科学技術フォーラム一般講演論文集 ( Forum on Information Technology ) 3 ( 3 ) 157 - 158 2004.08
カメラ同期・対応点の必要のない複数ステレオカメラのキャリブレーション法

飯塚健男, 中村恭之, 和田俊和

知能メカトロニクスワークショップ講演論文集 ( 〔精密工学会〕 ) 9 157 - 162 2004.08
ステレオカメラによるリアルタイム3次元位置計測システム

飯塚健男, 中村恭之, 和田俊和

画像の認識・理解シンポジウム(MIRU2004) デモセッション 312 2004.07 [Refereed]
Action planning of a wheeled mobile robot based on PaLM-tree

Kawahara T, Nakamura T, Wada T

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2004 142 - 142 2004.06
3-D Position Estimation of Color Targets Using Stereo Camera

IIZUKA Takeo, NAKAMURA Takayuki, WADA Toshikazu

IPSJ SIG Notes. CVIM ( 一般社団法人情報処理学会 ) 2004 ( 40 ) 65 - 70 2004.05

　View Summary

In the foregoing research of 3-dimensional depth measurement using stereo cameras, dense reconstruction of the object surface is mainly investigated. However, for the motion analysis and control of solid and/or articulated objects, it is sufficient to measure the 3-dimensional positions of several points on the object surfaces. In this paper, we propose a stereo camera system that estimates 3-dimensional position of multiple color targets in real time. We confirm the effectiveness of our system through the experiments that evaluate the performance of 3-dimensional position estimation.
非線形写像学習のためのPaLM-treeの提案とその応用

中村恭之, 加藤英介, 和田俊和

第9回ロボティクスシンポジア予稿集 360 - 366 2004.03 [Refereed]
画像情報と音情報から構成される状況提示システムに関する研究

中村恭之,堀内孝啓

文科省大大特プロジェクト第2回国際シンポジウム論文集 387-392 2004.01 [Refereed]
機械学習法のロボットへの応用

中村恭之

日本機械学会 03-90講習会教材:知能情報メカトロニクス研究最前線, 33-42 2003.12
ロボカップ中型機リーグ : 2050年に向けてのロードマップ

高橋泰岳, 松元明弘, 中村恭之

第4回 (社) 計測自動制御学会システムインテグレーション部門講演会概要集 3D5-3 2003.12
分散移動全方位視覚を用いた環境地図生成システムの開発(第1報)

中村恭之,堀内孝啓

第20回日本ロボット学会学術講演会資料集 3J14 2003.10
The New method for Generating a Map Based on the Interaction between a Robot's body and its Surrounding Environment

Uezu Yoshimi, Nakamura Takayuki, Wada Toshikazu

IPSJ SIG Notes. CVIM ( 一般社団法人情報処理学会 ) 2003 ( 41 ) 145 - 152 2003.05

　View Summary

So far, many researchers insisted that an environmental map is useful for navigating the robot and for generating robot's behaviors. As a result, there have been a variety of method for constructing the environmental map. Most of them focused on extracting the geometrical structure of the environment from the sensor information. To realize various robot's behaviors which come from the dynamic interaction between the robot and its surrounding environment, the acquisition of the inherent information in the environment, such as dynamical property of the environment is indispensable in addition...
車輪型移動ロボットの身体性に基づく動的行動の獲得

中村,和田

第8回ロボティクスシンポジア予稿集 522-526 2003.03 [Refereed]
Toward Knowledge Propagation in an omnidirectional Distributed Vision System

E.. Menegatti, E. Pagello, T. Minato, T. Nakamura, H. Ishiguro

1st International Workshop on Advances in Service Robotics (ASER'03) 2003.03 [Refereed]
Do computer vision techniques make soccer robot strong?

NAKAMURA TAKAYUKI

IPSJ SIG Notes. CVIM ( Information Processing Society of Japan (IPSJ) ) 2003 ( 2 ) 37 - 42 2003.01

　View Summary

In 1997, the first RoboCup competition was held. Small and middle-size robot league have been continued since 1997. In this paper, these two leagues are called the "robot leagues". This paper introduces how CV techniques are currently used in the robot leagues and states future problems.
Map generation based on the interaction between robot body and its surrounding environment

T. Nakamura, Y. Uezu, H. Wu, T. Wada

IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems ( Institute of Electrical and Electronics Engineers Inc. ) 2003- 70 - 75 2003 [Refereed]

　View Summary

This paper presents a method for map generation based on the interaction between a robot body and its surrounding environment. While a robot moves in the environment, the robot interacts with its surrounding environment. If the effect of the environment on the robot changes, such interactions also change. By observing the robot's body, our method detects such change of the interaction and generates a description representing the type of change and the location where such change is observed. In the current implementation, we assume that there are two types of the change in the interaction. The real robot experiments are conducted in order to show the validity of our method.

DOI
Automatic 2D Map Construction using a Special Catadioptric Sensor

T. Nakamura and H. Ishiguro

Proc. of IROS2002 196 - 201 2002.10 [Refereed]
身体的アプローチに基づいたマン-マシンコミュニケーション生成には何が必要か?

寺田,中村,伊藤

SI2002講演論文集 3A51-04 2002.10
Behavior Acquisition Method based on Embodiment for

K. Terada, T. Nakamura, H. Takeda

Proc. of IROS2002 964--969 2002.10 [Refereed]
Current Technical Issues and Future Work in the Real Robot League of RoboCup

NAKAMURA Takayuki

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 20 ( 1 ) 11 - 14 2002.01

DOI
Development of Adaptive Vision System

NAKAMURA Takayuki, MAEDA Tetsuhiro, OGASAWARA Tsukasa

電気学会研究会資料. SC, システム制御研究会 2001 ( 20 ) 31 - 34 2001.10
Omnidirectional Mobile Robot Navigation based on Omnidirectional Vision

NORIMATSU Yasuaki, TAKEMURA Kentaro, NAKAMURA Takayuki, OGASAWARA Tsukasa

電気学会研究会資料. SC, システム制御研究会 2001 ( 20 ) 25 - 29 2001.10
状態空間を更新する遺伝的プログラミング法によるサッカーエージェントの協調行動の獲得

中村恭之,山本哲也,小笠原司

第19回日本ロボット学会学術講演会予稿集 pp. 89-90 2001.09
Fast Self-Localization Method for Mobile Robots Using Multiple Ominidirectional Vision Sensors

NAKAMURA Takayuki, OHHARA Masahichi, OGASAWARA Tsukasa, ISHIGURO Hiroshi

IPSJ SIG Notes. CVIM ( 一般社団法人情報処理学会 ) 2001 ( 4 ) 133 - 138 2001.01

　View Summary

In the multi-agent environment, it is important to identify position and orientation of multiple robots for accomplishing a given task in cooperative manner. This paper proposes a method for estimating position and orientation of multiple robots using multiple omnidirectional images based on geometrical constraints. Our method reconstruct not only relative configuration between robots but also absolute one usign the knowledge of landmarks in the environment. Even if there are some obstacles in the environment, our method can estimate relative configuration between robots based on the result...
Continuous valued Q-learning method able to incrementally refine state space

M Takeda, T Nakamura, T Ogasawara

IROS 2001: PROCEEDINGS OF THE 2001 IEEE/RJS INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4 ( IEEE ) 265 - 271 2001 [Refereed]

　View Summary

The conventional reinforcement learning method has trouble in applying to real robot tasks, because such method must be able to represent the values in terms of infinitely many state and action pairs. In order to represent a action value function continuously, a function approximation method is usually applied. In our previous work [1], we pointed out that this type of learning method potentially has a discontinuity problem of optimal actions given a state.
In this paper, we propose a method for estimating where discontinuity of optimal action takes place and for refining a state space incrementally. We call this method an continuous valued Q-learning (hereafter, CVQ-learning) method. To show the validity of our method, we apply the method to a simulated robot.
Towards Cognitive Agents: Embodiement based Object Recognition for Vision-Based Mobile Agents

Kazunori Terada, Takayuki Nakamura, Hideaki Terada, Tsukasa Ogasawara

Prof. of 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'2000) 2067-2072 2000.11 [Refereed]
対象認識のための接触に基づく効用関数の生成 (小特集身体性)

寺田和憲, 中村恭之, 小笠原司

人工知能基礎論研究会 ( 人工知能学会 ) 42 45 - 50 2000.09
複数の全方位画像を用いた実時間自己位置同定

大原正満、海老名明弘、中村恭之、今井正和、小笠原司、石黒浩

第18回ロボット学会学術講演会予稿集 1225 - 1226 2000.09
Embodiment based Object Recognition

TERADA Kazunori, NAKAMURA Takayuki, TAKEDA Hideaki, OGASAWARA Tsukasa

Proceedings of the Annual Conference of JSAI ( 人工知能学会 ) 14 508 - 511 2000.07

　View Summary

In order to keep visual tracking systems with color segmentation technique running in real environment, it should be developed on-line learning method to update models for adapting them to dynamic changes of surroundings. To deal with this problem, we propose an on-line visual learning method for color image segmentation and object tracking in dynamic environment. Our method utilizes Fuzzy ART architecture which is a kind of neural network for competitive learning. The mechanism of this neural network is suitable for on-line learning and different from that of backpropagation type neural...
複数の全方位画像を用いた実時間自己位置同定

海老名明弘, 中村恭之, 今井正和, 小笠原司

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2A1-67-090 72 - 72 2000.05

　View Summary

複数の移動ロボットに搭載した全方位カメラを用いた実時間自己位置同定手法について述べる。各移動ロボットにおいて得られた全方位画像を床面上への画像に変換し, 線分を検出する。検出された線分とゴールの方向や位置情報を用いて定量的な自己位置同定を行う。複数のロボット間でこれらの情報を交換する事で, 各ロボットの自己位置やロボット間の相対的な位置関係を実時間で同定した。サッカーロボットを用いて行った実験結果について述べると共に, 問題点と今後の課題について述べる。
身体性に基づく環境モデリングと行動生成

寺田和憲,中村恭之,武田英明,小笠原司

第5回ロボティクスシンポジア予稿集 92 - 97 2000.03 [Refereed]
最適行動の不連続問題を考慮したContinuous Valued Q-learningの提案

武田政宣,中村恭之,今井正和,小笠原司,浅田稔

第5回ロボティクスシンポジア予稿 409 - 414 2000.03 [Refereed]
Toward a Visual Tracking System with On-Line Visual Learning Capability

NAKAMURA T.

Journal of Robotics Society of Japan 18 ( 7 ) 1047 - 1054 2000
Enhanced continuous valued Q-learning for real autonomous robots

M Takeda, T Nakamura, M Imai, T Ogasawara, M Asada

Proc. of Int. Conf. of The Society for Adaptive Behavior 2000 ( VSP BV ) 195 - 202 2000 [Refereed]

DOI
Real-time estimating spatial configuration between multiple robots by triangle and enumeration constraints

T. Nakamura, A. Ebina, M. Imai, T. Ogasawara, H. Ishiguro

IEEE International Conference on Intelligent Robots and Systems 3 2048 - 2054 2000 [Refereed]

　View Summary

In the multi-agent environment, it is important to identify position and orientation of multiple robots for accomplishing a given task in cooperative manner. This paper proposes a method for estimating position and orientation of multiple robots using multiple omnidirectional images based on geometrical constraints. Our method reconstruct not only relative configuration between robots but also absolute one using the knowledge of landmarks in the environment. Even if there are some obstacles in the environment, our method can estimate absolute configuration between robots based on the results of self-localization of each robot.

DOI
ロボットサッカー研究のためのシミレーター開発

藤原広光,中村恭之,今井正和,小笠原司

第17回日本ロボット学会学術講演会予稿集 255 - 256 1999.09
RoboCup '98パリ大会

中村恭之

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 17 ( 5 ) 643 - 644 1999.07

DOI
A Nonholonomic Mobile Robot Navigation in Unknown Environment

FUJII Hirokazu, HIRANO Masatoshi, NAKAMURA Takayuki, MATSUMOTO Yoshio, IMAI Masakazu, OGASAWARA Tsukasa

電気学会研究会資料. SC, システム制御研究会 1999 ( 11 ) 35 - 40 1999.03
Mobile Robot Navigation in a Dynamic Environment using KL Expansion of Omnidirectional Images

SHIBATA Atsushi, NAKAMURA Takayuki, MATSUMOTO Yoshio, IMAI Masakazu, OGASAWARA Tsukasa

電気学会研究会資料. SC, システム制御研究会 1999 ( 11 ) 41 - 46 1999.03
色情報に基づくラベリング処理LSIの開発とその応用

秋田純一,渡辺晃,中村恭之,小笠原

第４回ロボティクスシンポジア予稿集 189 - 194 1999.03 [Refereed]
実時間競合学習モデルFuzzy ARTを用いたカラー画像の領域分割と追跡

中村恭之,小笠原司

第4回ロボティクスシンポジア 183 - 188 1999.03 [Refereed]
Why is cognitive robotics promising?

NAKAMURA Takayuki, SATO Tomomasa, KUNIYOSHI Yasuo, HIRAKI Kazuo, SHIBATA Tomohiro, ASADA Minoru, MACDORMAN Karl F, TANI Jun

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 17 ( 1 ) 38 - 43 1999.01

DOI
On-Line Visual Learning Method for Color Image Segmentation and Object Tracking

NAKAMURA T.

Proc. of IROS'99 222 - 228 1999 [Refereed]
システム同定アプローチに基づくロボット学習---移動ロボットの行動獲得問題への応用---

中村,小笠原,

第17回ロボット学会学術講演会予稿集 1007 - 1008 1999
システム同定アプローチに基づくロボット学習---視覚情報に基づく地図学習への応用---

中村,海老名,藤原,小笠原

ロボティクス・メカトロニクス講演会'99講演論文集 2P1-24-007 1999
On-Line Visual Learning Method for Color Image Segmentation and Object Tracking

NAKAMURA Takayuki

人工知能学会全国大会論文集 = Proceedings of the Annual Conference of JSAI 12 89 - 91 1998.06
ロボットサッカー研究のための安価な視覚移動ロボットの開発

中村恭之ほか

第3回JSMEロボメカ・シンポジア 89 - 91 1998
Development of Self-Learning Vision-Based Mobile Robots for Acquiring Soccer Robots Behaviors

T. Nakamura

Distributed Autonomous Robotic Systems 3, Springer-Verlag 101 - 110 1998 [Refereed]
Development of a Cheap On-board Vision Mobile Robot for Robotic Soccer Research

NAKAMURA T.

Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 1998 431 - 436 1998 [Refereed]
ロボットサッカー研究のための安価な視覚移動ロボットの開発

中村恭之ほか

第3回ロボティクス・シンポジア 31 - 36 1998 [Refereed]
移動ロボットの誘導のためのステレオ視による環境表現

福西,中村,今井,小笠原

第16回日本ロボット学会学術講演会 1515 - 1516 1998
Self-organizing internal representation for behavior acquisition of vision-based mobile robots

NAKAMURA T.

Proceedings of the foruth International Conference on Simulation of Adaptive Behaivior : From Animals to Animats 5 104 - 113 1998 [Refereed]
Development of Self-Learning Vision-Based Mobile Robots for Acquiring Soccer Robots Behaviors

T. Nakamura

Proc. of IEEE Int. Conf. on Robotics and Automation 2592 - 2598 1998 [Refereed]
全方位画像情報に基づく非ホロノミック移動ロボットの誘導

藤井,中村,今井,小笠原

第16回日本ロボット学会学術講演会 797 - 798 1998
The RoboCup-NAIST: A Cheap Multisensor-Based Mobile Robot with On-Line Visual Learning Capability

Takayuki Nakamura

Proc. of RoboCup-98 Workshop 291 - 303 1998 [Refereed]
Development of Self-Learning Vision-Based Mobile Robots for Acquiring Soccer Robots Behaviors

T. Nakamura

The First Robot World Cup Soccer Games and Conferences 1997, Springer-Verlag 248 - 268 1997 [Refereed]
視覚移動ロボットのタスク達成のための状態空間の自律的構成手法

中村恭之

第15回ロボット学会学術講演会予稿集 139 - 140 1997
Correlation-Based Visual Tracking enhanced by Affine Motion Description

Adachi Yoshihisa, Nakamura Takayuki, Asada Minoru

IPSJ SIG Notes. CVIM ( Information Processing Society of Japan (IPSJ) ) 96 ( 47 ) 101 - 106 1996.05

　View Summary

Tracking a target by conventional correlation-based algorithm with a single reference image often fails on the following situation: 1) a view of the target image changes. 2) a part of the target image is occluded. In this paper, we propose a method of correlation-based visual tracking enhanced by affine motion description. Multiple tracking windows are utilized for tracking a target. The motion of the tracked region is described by multiple motion vectors each of which obtained from each tracking window, and it is approximated by an affine motion model. Based on the estimated parameters of ...
Behavior Acquisition via Vision-Based Robot Learning

M. Asada, T. Nakamura and K. Hosoda,

Robotics Research, The Seventh International Symosium, Springer 279 - 286 1996 [Refereed]
Direct coupling of multisensor information and actions for mobile robot behavior acquisition

T. Nakamura, J. Morimoto, and M. asada.

Proc. of IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems 139 - 144 1996 [Refereed]
Correlation-based visual tracking enhanced by affine motion description

ADACHI Y.

Proc. Workshop on Machine Vision and Applications 75 - 78 1996 [Refereed]
Target Reaching Behavior Learning with Occlusion Detection and Avoidance for A Stereo Vision-Based Mobile Robot

M. Asada and T. Nakamura

Proc. of ROBOLEARN96: An International Workshop on Learning for Autonomous Robots 1996 [Refereed]
Stereo Sketch: Stereo Vision-Based Target Reaching Behavior Acquisition with Occlusion Detection and Avoidance

T. Nakamura and M. Asada

Proc. of IEEE Int. Conf. on Robotics and Automation 1314 - 1319 1996 [Refereed]
センサー系と行動系に基づいた移動ロボットの環境構造の獲得

高村,中村,浅田

第14回ロボット学会学術講演会予稿集 177 - 178 1996
Motion Sketch : Acquisition of Visual Motion Guided Behaviors

NAKAMURA Takayuki, ASADA Minoru

人工知能学会全国大会論文集 = Proceedings of the Annual Conference of JSAI 9 561 - 564 1995.07
How To Bring Up A One-Eyed Mobile Robo-Infant

T. Nakamura and M. Asada,

Proc. of Int. Workshop on Biologically Inspired Evolutionary Systems 1995 [Refereed]
画像運動情報に基づく単眼視覚移動ロボットの行動獲得

中村,浅田

第5回ロボットシンポジウム予稿集 1995 [Refereed]
Acquisition of Visual Motion Guided Behaviors

M. Asada and T. Nakamura

Proc. of Information Integration Workshop 1995 [Refereed]
ステレオ視覚を持つ移動ロボットの目標到達行動におけるオクルージョン回避行動の獲得

中村,浅田

第13回ロボット学会学術講演会予稿集 1995
Vision-Based Robot Learning for Behavior Acquisition

M. Asada, T. Nakamura, and K. Hosoda

Proc. of IROS95 Workshop on Vision for Robots 1995 [Refereed]
Motion Sketch: Acquisition of Visual Motion Guided Behaviors

T. Nakamura and M. Asada

Proc. of Int. Joint Conference on Aritificial Intelligence 1995 [Refereed]
視覚を持つ移動ロボットの障害物回避行動の獲得

中村,浅田,細田

第12回日本ロボット学会学術講演会予稿集 409 - 410 1994
Cylindrical Shape from Contour and Shading without Knowledge of Lighting Conditions or Surface Albedo

ASADA Minoru, NAKAMURA Takayuki

IPSJ Journal ( Information Processing Society of Japan (IPSJ) ) 34 ( 5 ) 884 - 891 1993.05

　View Summary

This paper presents and algorithm for reconstructiong the shape of a cylindrical object from contour and shading without knowing the surface albedo of the object of the lighting conditions of the scene. Input image is segmented into spherical, cylindrical, or planar surfaces by analyzing local shading. The cylindrical surface is characterized with a direction of generationg lines determined from spatial derivatives in the image. The brightest generating line has strong constraints on both the shading analysis on the cylindrical surface and a simplification of the equation which represents the relation between the contour shape and shading. Although there remains one degree of freedom between the surface normal of the base plane and the slant angle of the generating line, we can uniquely recover the cylindrical shape from this solution. Experimental results for both synthetic and real images are shown.
A qualitative approach to quantitative recovery of shgc's shape and pose from shading and contour

Takayuki Nakamura, Yoshiaki Shirai, and Minoru Asada

Proceeding of IEEE Computer Society Conference on CVPR 116 - 122 1993 [Refereed]
Weak Lambertian Assumption for Determining Cylindrical Shape and Pose from Shading and Contour

ASADA M.

Proc. of CVPR '92 726 - 729 1992 [Refereed]
A qualitative approach to quantitative recovery of Cylindrical Shape, Pose and Illuminant Condition from Shading and Contour

NAKAMURA T.

Proc of IROS'92 1223 - 1230 1992 [Refereed]

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Awards & Honors

2023年度計測自動制御学会SI部門貢献表彰

2023.12 計測自動制御学会SI部門第28回ロボティクスシンポジアプログラム委員長として貢献
日本ロボット学会功労賞

Winner：第25回ロボティクスシンポジアでの運営

2021.09 日本ロボット学会
第17回計測自動制御学会システムインテグレーション部門講演会(SI2016)優秀講演賞

2016 計測自動制御学会

　View Summary

12月，国内受賞，古典舞踊動作の手先軌道に着目した優美さの定量化
第２回HSSデザインコンテスト2014 優秀賞

2014 日本知能情報ファジイ学会

　View Summary

3月8日，国内受賞，力学的操作による意図認識に基づく倒立二輪型ロボットの制御

Patents

カメラキャリブレーション装置及び方法

Patent no： 3849030

Date registered： 2006.09.08

Date applied： 2004.04.23 （特願2004-128502 ） Publication date： 2005.11.04 （特開2005-308641 ）

Inventor(s)/Creator(s)：中村恭之、和田俊和、飯塚健男 Applicant：国立大学法人和歌山大学
非線形写像学習コンピュータプログラム、および記録媒体

Date applied： 2005.05.31 （特願2005-159328 ） Publication date： 2006.12.14 （特開2006-338123 ）

Inventor(s)/Creator(s)：中村恭之、和田俊和 Applicant：国立大学法人和歌山大学

KAKENHI

3D LIDARからの複数物体点群データの自動補間システムの構築とその応用

2020.04

-

2023.03

Grant-in-Aid for Scientific Research(C) Principal investigator
舞踊動作を規範とした「優美さ」特徴のモデル化-動きとフォルムの両側面から迫る-

2017.04

-

2020.03

Grant-in-Aid for Scientific Research(C) Co-investigator
一人乗り電気自動車を対象とした不整地走行戦略の自動学習システムの研究

2017.04

-

2020.03

Grant-in-Aid for Scientific Research(C) Principal investigator
屋外環境下の果樹等を対象とした非定常物体モデリングシステムの研究

2014.04

-

2017.03

Grant-in-Aid for Scientific Research(C) Principal investigator
動作における「優美さ」評価方法の確立－「美の線」を基準とした計測・評価－

2014.04

-

2017.03

Grant-in-Aid for Scientific Research(C) Co-investigator
三次元視覚システムのためのシームレスな対象モデリングシステムの研究

2011.04

-

2014.03

Grant-in-Aid for Scientific Research(C) Principal investigator
「優美な」動作のモデル化とロボット「優美」動作生成法の確立

2011.04

-

2014.03

Grant-in-Aid for Scientific Research(C) Co-investigator
次世代ロボットのためのデータ取得・選択機能を有するデータマイニング

2008.04

-

2011.03

Grant-in-Aid for Scientific Research(C) Principal investigator
非線形システムの事例に基づく逐次学習可能なモデリング手法の構築とその応用

2004.04

-

2006.03

Grant-in-Aid for Young Scientists(B) Principal investigator
状況に依存して内部構造を変化する視覚情報処理システムに関する研究

2000.04

-

2002.03

奨励研究（A） Principal investigator

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Public Funding (other government agencies of their auxiliary organs, local governments, etc.)

多様体学習に基づく人間型ロボットの全身運動パターン生成法に関する研究

2007.04

-

2010.03

Principal investigator

Instructor for open lecture, peer review for academic journal, media appearances, etc.

非常勤講師

2022.04.01

-

2024.03.31

東京医療保健大学

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非常勤講師

本学講義　前期「パーソナル・コンピューター入門」8回
「情報リテラシー」10回
後期「情報科学概論」8回
非常勤講師

2022.04.01

-

2024.03.31

学校法人明浄学院　大阪観光大学

　View Details

非常勤講師

前期：「ICT基礎１（再）／情報処理基礎演習Ａ」
後期：「ICT基礎２（再）／情報処理基礎演習Ｂ」
前期：「ICT基礎１（再）／情報処理基礎演習Ａ」
後期：「ICT基礎２（再）／情報処理基礎演習Ｂ」

３限：１３：２０～１４：５０
４限：１５：００～１６：３０
自動溶接技術開発にかかる技術指導・助言

2021.08.01

-

2021.10.31

三菱重工業株式会社原子力セグメント原子力工作部

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助言・指導

自動溶接開発業務における
深層学習および画像取得・処理に関する技術指導・助言業務
非常勤講師

2021.04.01

-

2022.03.31

東京医療保健大学

　View Details

非常勤講師

非常勤講師として以下2科目を担当していただく。
・「情報リテラシー」２０２０／５／２２、５／２９、６／５、６／１２、６／１９、６／２６、７／３、７／１０、７／１７、７／３１実施
・「情報科学」２０２０／１０／７、１０／１４、１０／２１、１０／２８、１１／４、１１／１１、１１／１８、１１／２５、１２／２、１２／９、１２／１６、１２／２３、２０２１／１／６、１／１３、１／２０実施
非常勤講師

2021.04.01

-

2022.03.18

学校法人　明浄学院　大阪観光大学

　View Details

非常勤講師

非常勤講師として「情報処理基礎演習A」の講義を前期月曜3、4時限に、「情報処理基礎演習B」を後期月曜3、4限を担当する。
非常勤講師

2020.10.31

-

2021.01.09

大阪電気通信大学

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非常勤講師

「コンピュータハードウエア」後期（土曜集中）の講義を行う。
１０／３１（土）１～４限、１１／２８（土）１～４限、
１２／１２（土）１～４限、１／９（土）１～３限
AI自動溶接技術開発支援コンサル

2020.05.25

-

2021.02.26

三菱重工業株式会社　原子力セグメント原子力工作部

　View Details

助言・指導

自動溶接技術開発における
深層学習および画像処理の観点でのコンサル業務
非常勤講師

2020.04.01

-

2021.03.31

東京医療保健大学

　View Details

非常勤講師

非常勤講師として以下2科目を担当していただく。
・「情報リテラシー」２０２０／５／２２、５／２９、６／５、６／１２、６／１９、６／２６、７／３、７／１０、７／１７、７／３１実施
・「情報科学」２０２０／１０／７、１０／１４、１０／２１、１０／２８、１１／４、１１／１１、１１／１８、１１／２５、１２／２、１２／９、１２／１６、１２／２３、２０２１／１／６、１／１３、１／２０実施
非常勤講師

2020.04.01

-

2021.03.18

学校法人　明浄学院　大阪観光大学

　View Details

非常勤講師

非常勤講師として「情報処理基礎演習A」の講義を前期月曜3、4時限に、「情報処理基礎演習B」を後期月曜3、4限を担当する。
非常勤講師

2019.10

-

2020.03

東京医療保健大学

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非常勤講師等

非常勤講師,任期:2019年10月～2020年3月
非常勤講師

2019.09

-

2020.03

大阪電気通信大学

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非常勤講師等

非常勤講師,任期:2019年9月～2020年3月
非常勤講師

2019.04

-

2019.09

国立大学法人福井大学

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非常勤講師等

非常勤講師,任期:2019年4月～2019年9月
非常勤講師

2019.04

-

2019.09

東京医療保健大学

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非常勤講師等

非常勤講師,任期:2019年4月～2019年9月
非常勤講師

2018.10

-

2019.03

東京医療保健大学

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非常勤講師等

非常勤講師,任期:2018年10月～2019年3月
非常勤講師

2018.09

-

2019.03

大阪電気通信大学

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非常勤講師等

非常勤講師,任期:2018年9月～2019年3月
講師

2018.07

-

Now

開智中学校・高等学校進路研究会

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講演講師等

講師,任期:2018年7月～
非常勤講師

2018.04

-

2018.09

東京医療保健大学

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非常勤講師等

非常勤講師,任期:2018年4月～2018年9月
開智オープンセミナー

2018.04

開智高校

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公開講座・講演会の企画・講師等

最新の人工知能・ロボット研究の紹介,日付:2018年7月
オープンキャンパス

2018.04

和歌山大学

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公開講座・講演会の企画・講師等

研究室の主要研究の紹介,日付:7月
非常勤講師

2017.09

-

2018.03

大阪電気通信大学

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非常勤講師等

非常勤講師,任期:2017年９月～2018年３月
非常勤講師

2017.04

-

2018.03

独立行政法人国立高等専門学校機構　奈良工業高等専門学校

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非常勤講師等

非常勤講師,任期:2017年４月～2018年３月
高専生向けインターンシップ

2017.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ROSを用いたロボットプログラミング」について高専生に解説,日付:8月
オープンキャンパス

2017.04

和歌山大学

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公開講座・講演会の企画・講師等

研究室の主要研究の紹介,日付:7月16日
非常勤講師

2016.09

-

2017.03

大阪電気通信大学

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非常勤講師等

非常勤講師,任期:2016年9月-2017年3月
講師

2016.07

-

Now

進路研究会「開智オープンセミナー」

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講演講師等

講師
非常勤講師

2016.04

-

2017.03

独立行政法人国立高等専門学校機構　奈良工業高等専門学校

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非常勤講師等

非常勤講師,任期:2016年4月-2017年3月
海南高校SSH課外授業

2016.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ロボットの仕組み」について高校生に解説,日付:12月13日
高専生向けインターンシップ

2016.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ROSを用いたロボットプログラミング」について高専生に解説,日付:8月
開智オープンセミナー

2016.04

開智高校

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公開講座・講演会の企画・講師等

最新の人工知能・ロボット研究の紹介,日付:2016年7月9日
オープンキャンパス

2016.04

和歌山大学

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公開講座・講演会の企画・講師等

研究室の主要研究の紹介,日付:7月17日
非常勤講師

2015.09

-

2016.03

大阪電気通信大学

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非常勤講師等

非常勤講師,任期:2015/09/16～2016/03/15
非常勤講師

2015.04

-

2016.03

奈良工業高等専門学校

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非常勤講師等

非常勤講師,任期:2015/04/01～2016/03/31
オープンキャンパス

2015.04

和歌山大学

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公開講座・講演会の企画・講師等

研究室の主要研究の紹介,日付:7月19日
高津高校研究室訪問

2014.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ロボットの仕組み」について高校生に解説,日付:11月11日
地域創造への連携2015

2014.04

和歌山大学・和歌山大学地域創造支援機構

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公開講座・講演会の企画・講師等

独創的研究プロジェクトの成果発表,日付:2015年2月19日
オープンキャンパス

2014.04

和歌山大学

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公開講座・講演会の企画・講師等

研究室の主要研究の紹介,日付:7月20日
高津高校研究室訪問

2013.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ロボットの仕組み」について高校生に解説,日付:7月16日
地域創造への連携2014

2013.04

和歌山大学・和歌山大学地域創造支援機構

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公開講座・講演会の企画・講師等

独創的研究プロジェクトの成果発表,日付:2014年2月12日
開智オープンセミナー

2012.04

その他

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小・中・高校生を対象とした学部体験入学・出張講座等

「ロボットの仕組み」について高校生に解説,日付:7月14日

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Committee member history in academic associations, government agencies, municipalities, etc.

第28回ロボティクスシンポジア・プログラム委員長

2022.04

-

2023.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第28回ロボティクスシンポジアのプログラム委員長を務め，
表彰委員も同時に担当した．
第27回ロボティクスシンポジア・プログラム副委員長

2021.10

-

2022.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第27回ロボティクスシンポジアのプログラム副委員長を務め，
表彰委員も同時に担当した．
日本ロボット学会・代議員

2021.01

-

Now

日本ロボット学会

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代議員

代議員を務める
第26回ロボティクスシンポジア・プログラム委員

2020.10

-

2021.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第26回ロボティクスシンポジアのプログラム委員を務めた
第25回ロボティクスシンポジアPC委員

2019.10

-

2020.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第25回ロボティクスシンポジアのプログラム委員を務めた
審査員

2019.07

-

Now

和歌山県　令和元年度先駆的産業技術研究開発支援事業の事業選定に係る書面審査

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国や地方自治体、他大学・研究機関等での委員

審査員,任期:2019年7月～
代議員

2019.04

-

2020.04

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員
第24回ロボティクスシンポジアPC委員

2018.10

-

2019.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第24回ロボティクスシンポジアのプログラム委員を務めた
審査員

2018.07

-

Now

平成30年度先駆的産業技術研究開発支援事業の事業選定に係る書面審査

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国や地方自治体、他大学・研究機関等での委員

審査員,任期:2018年7月～
委員

2018.06

-

2019.03

三菱重工業株式会社パワードメイン原子力事業部技術開発における有識者検討会

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国や地方自治体、他大学・研究機関等での委員

委員,任期:2018年6月～2019年3月
代議員

2018.04

-

2019.04

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員
書面審査

2017.10

-

Now

平成29年度先駆的産業技術研究開発支援事業の事業選定に係る書面審査

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国や地方自治体、他大学・研究機関等での委員

書面審査,任期:2017年１０月～
第23回ロボティクスシンポジアPC委員

2017.10

-

2018.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第23回ロボティクスシンポジアのプログラム委員を務めた
有識者委員

2017.07

-

2018.03

経済産業省　原子力の安全性向上に資する技術開発費補助金（製造技術の高度化）有識者検討会

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国や地方自治体、他大学・研究機関等での委員

有識者委員,任期:2017年７月～2018年３月
代議員

2017.04

-

2018.04

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員
第22回ロボティクスシンポジアPC委員

2016.10

-

2017.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第22回ロボティクスシンポジアのプログラム委員を務めた
第21回ロボティクスシンポジアPC委員

2015.10

-

2016.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第21回ロボティクスシンポジアのプログラム委員を務めた
専門委員

2014.12

-

2015.11

科学研究費委員会

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国や地方自治体、他大学・研究機関等での委員

専門委員,任期:2014/12/01～2015/11/30
第20回ロボティクスシンポジアPC委員

2014.10

-

2015.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第20回ロボティクスシンポジアのプログラム委員を務めた
委員

2013.12

-

2014.11

基盤研究等第１段審査委員

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国や地方自治体、他大学・研究機関等での委員

国や地方自治体、他大学・研究機関等での委員,任期:2013/12/01～2014/11/30
第19回ロボティクスシンポジアPC委員

2013.10

-

2014.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第19回ロボティクスシンポジアのプログラム委員を務めた
委員

2013.04

-

2014.03

公益社団法人商事法務研究会　　適性試験管理委員会適性試験管理委員会委員

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国や地方自治体、他大学・研究機関等での委員

国や地方自治体、他大学・研究機関等での委員,任期:2013/04/17～2014/03/31
第18回ロボティクスシンポジアPC委員

2012.10

-

2013.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第18回ロボティクスシンポジアのプログラム委員を務めた
第17回ロボティクスシンポジアPC委員

2011.10

-

2012.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第17回ロボティクスシンポジアのプログラム委員を務めた
第16回ロボティクスシンポジアPC委員

2010.10

-

2011.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第16回ロボティクスシンポジアのプログラム委員を務めた
第5地区(関西地区)の地区技術委員会委員長

2010.04

-

2011.03

機械学会ロボティクスメカトロニクス部門

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2010.4～2011.3
第25回研究奨励賞選考委員会委員

2009.12

-

2010.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2009.12～2010.3
評議員

2009.04

-

2011.04

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2009.4～2011.4
第15回ロボティクスシンポジア実行委員

2009.04

-

2010.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

第15回ロボティクスシンポジアの実行委員を務め,会議運営に尽力した.,任期:2009.4～2010.3
第5地区(関西地区)の地区技術委員会副委員長

2009.03

-

2010.03

機械学会ロボティクスメカトロニクス部門

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国や地方自治体、他大学・研究機関等での委員

第5地区(関西地区)の地区技術委員会副委員長 ,任期:2009.3～2010.3
第24回研究奨励賞選考委員会委員

2008.12

-

2009.03

日本ロボット学会

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学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2008.12～2009.3

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Other Social Activities

後援会システム工学部支部総会

2022.04

-

2023.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2021.04

-

2022.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2020.04

-

2021.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2019.04

-

2020.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2018.04

-

2019.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2017.04

-

2018.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2016.04

-

2017.03

その他

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社会との連携を推進する活動

総会に参加
後援会システム工学部支部総会

2015.04

-

2016.03

その他

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社会との連携を推進する活動

総会に参加
学部創立20周年記念式典・祝賀会

2015.04

-

2016.03

その他

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社会との連携を推進する活動

式典・祝賀会に参加

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