PUBLICATIONSPEOPLE

Journals

  • N. Hosomi, S. Hatanaka, Y. Iioka, W. Yang, K. Kuyo, T. Misu, K. Yamada, and K. Sugiura, “Trimodal Navigable Region Segmentation Model: Grounding Navigation Instructions in Urban Areas”, IEEE Robotics and Automation Letters, 2024, to appear.
  • K. Kaneda, S. Nagashima, R. Korekata, M. Kambara, and K. Sugiura, “Learning-To-Rank Approach for Identifying Everyday Objects Using a Physical-World Search Engine”, IEEE Robotics and Automation Letters, Vol. 9, Issue 3, pp. 2088-2095, 2024. DOI: 10.1109/LRA.2024.3352363PDF
  • A. Ueda, W. Yang and K. Sugiura, “Switching Text-Based Image Encoders for Captioning Images With Text”, IEEE Access, Vol. 11, pp. 55706-55715, 2023. DOI: 10.1109/ACCESS.2023.3282444PDF
  • S. Ishikawa and K. Sugiura, “Affective Image Captioning for Visual Artworks Using Emotion-Based Cross-Attention Mechanisms”, IEEE Access, Vol. 11, pp. 24527-24534, 2023. DOI: 10.1109/ACCESS.2023.3255887PDF
  • S. Matsumori, Y. Abe, K. Shingyouchi, K. Sugiura, and M. Imai, “LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned Image Manipulation”, IEEE Access, Vol. 9, pp. 160521-160532, 2021. DOI: 10.1109/ACCESS.2021.3129215PDF
  • M. Kambara and K. Sugiura, “Case Relation Transformer: A Crossmodal Language Generation Model for Fetching Instructions”, IEEE Robotics and Automation Letters, Vol. 6, Issue 4, pp. 8371-8378, 2021. DOI: 10.1109/LRA.2021.3107026PDF
  • S. Ishikawa and K. Sugiura, “Target-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots”, IEEE Robotics and Automation Letters, Vol. 6, Issue 4, pp. 8401-8408, 2021. DOI: 10.1109/LRA.2021.3108500PDF
  • A. Magassouba, K. Sugiura, and H. Kawai, “CrossMap Transformer: A Crossmodal Masked Path Transformer Using Double Back-Translation for Vision-and-Language Navigation”, IEEE Robotics and Automation Letters, Vol. 6, Issue 4, pp. 6258-6265, 2021. DOI: 10.1109/LRA.2021.3092686PDF
  • A. Magassouba, K. Sugiura, A. Nakayama, T. Hirakawa, T. Yamashita, H. Fujiyoshi, and H. Kawai, “Predicting and Attending to Damaging Collisions for Placing Everyday Objects in Photo-Realistic Simulations”, Advanced Robotics, Vol. 35, Issue 12, pp. 787-799, 2021. DOI: 10.1080/01691864.2021.1913446PDF
  • N. Nishizuka, Y. Kubo, K. Sugiura, M. Den, M. Ishii, “Operational Solar Flare Prediction Model Using Deep Flare Net”, Earth, Planets and Space, Vol. 73, Article 64, pp. 1-12, 2021. DOI: 10.1186/s40623-021-01381-9PDF
  • T. Ogura, A. Magassouba, K. Sugiura, T. Hirakawa, T. Yamashita, H. Fujiyoshi, H. Kawai, “Alleviating the Burden of Labeling: Sentence Generation by Attention Branch Encoder-Decoder Network”, IEEE Robotics and Automation Letters, Vol. 5, Issue 4, pp. 5945-5952, 2020. DOI: 10.1109/LRA.2020.3010735PDF
  • N. Nishizuka, Y. Kubo, K. Sugiura, M. Den, M. Ishii, “Reliable Probability Prediction Model of Solar Flares: Deep Flare Net-Reliable (DeFN-R)”, The Astrophysical Journal, Vol. 899, No. 2, 150(8pp), 2020. DOI: 10.3847/1538-4357/aba2f2PDF
  • A. Magassouba, K. Sugiura, H. Kawai, “A Multimodal Target-Source Classifier with Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects”, IEEE Robotics and Automation Letters, Vol. 5, Issue 2, pp. 532-539, 2020. DOI: 10.1109/LRA.2019.2963649PDF
  • A. Magassouba, K. Sugiura, A. Trinh Quoc, H. Kawai, “Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification”, IEEE Robotics and Automation Letters, Vol. 4, Issue 4, pp. 3884 – 3891, 2019. DOI: 10.1109/LRA.2019.2926223PDF
  • A. Magassouba, K. Sugiura, H. Kawai, “A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions”, IEEE Robotics and Automation Letters, Vol. 3, Issue 4, pp. 3113-3120, 2018. DOI: 10.1109/LRA.2018.2849607PDFSlides
  • K. Sugiura, “SuMo-SS: Submodular Optimization Sensor Scattering for Deploying Sensor Networks by Drones”, IEEE Robotics and Automation Letters, Vol. 3, Issue 4, pp. 2963-2970, 2018. DOI: 10.1109/LRA.2018.2849604PDFSlides
  • N. Nishizuka, K. Sugiura, Y. Kubo, M. Den, and M. Ishii, “Deep Flare Net (DeFN) Model for Solar Flare Prediction”, The Astrophysical Journal, Vol. 858, Issue 2, 113 (8pp), 2018. DOI: 10.3847/1538-4357/aab9a7PDF
  • 奥川雅之, 伊藤暢浩, 岡田浩之, 植村渉, 高橋友一, 杉浦孔明, “ロボカップ西暦2050年を目指して”, 知能情報ファジィ学会誌, Vol. 29, No.2, pp. 42-54, 2017.
  • T. Nose, Y. Arao, T. Kobayashi, K. Sugiura, and Y. Shiga, “Sentence Selection Based on Extended Entropy Using Phonetic and Prosodic Contexts for Statistical Parametric Speech Synthesis”, IEEE Transactions on Audio, Speech, and Language Processing, Vol. 25, Issue 5, pp. 1107-1116, 2017.PDF
  • N. Nishizuka, K. Sugiura, Y. Kubo, M. Den, S. Watari and M. Ishii, “Solar Flare Prediction Model with Three Machine-learning Algorithms using Ultraviolet Brightening and Vector Magnetogram”, The Astrophysical Journal, Vol. 835, Issue 2, 156 (10pp), 2017.PDF
  • S. Takeuchi, K. Sugiura, Y. Akahoshi, and K. Zettsu, “Spatio-Temporal Pseudo Relevance Feedback for Scientific Data Retrieval,” IEEJ Trans., Vol. 12, Issue 1, pp. 124-131, 2017.PDF
  • K. Lwin, K. Sugiura, and K. Zettsu, “Space-Time Multiple Regression Model for Grid-Based Population Estimation in Urban Areas,” International Journal of Geographical Information Science, Vol. 30, No. 8, pp. 1579-1593, 2016.
  • 杉浦孔明, “模倣学習における確率ロボティクスの新展開”, システム制御情報学会誌, Vol. 60, No. 12, pp. 521-527, 2016.PDF
  • 杉浦孔明, “ロボットによる大規模言語学習に向けて -実世界知識の利活用とクラウドロボティクス基盤の構築-“, 計測と制御, Vol. 55, No. 10, pp. 884-889, 2016.PDF
  • 杉浦孔明, “ビッグデータの利活用によるロボットの音声コミュニケーション基盤構築”, 電子情報通信学会誌, Vol. 99, No. 6, pp. 500-504, 2016.PDF
  • B. T. Ong, K. Sugiura, and K. Zettsu, “Dynamically Pre-trained Deep Recurrent Neural Networks using Environmental Monitoring Data for Predicting PM2.5,” Neural Computing and Applications, Vol. 27, Issue 6, pp. 1553–1566, 2016.PDF
  • 杉浦孔明, “ロボカップ＠ホーム: 人と共存するロボットのベンチマークテスト”, 人工知能, Vol. 31, No. 2, pp. 230-236, 2016.PDF
  • L. Iocchi, D. Holz, J. Ruiz-del-Solar, K. Sugiura, and T. van der Zant, “RoboCup@Home: Analysis and Results of Evolving Competitions for Domestic and Service Robots,” Artificial Intelligence, Vol. 229, pp. 258-281, 2015.
  • K. Sugiura, Y. Shiga, H. Kawai, T. Misu and C. Hori, “A Cloud Robotics Approach towards Dialogue-Oriented Robot Speech,” Advanced Robotics, Vol. 29, Issue 7, pp. 449-456, 2015.PDF
  • 杉浦孔明, 岩橋直人, 芳賀麻誉美, 堀智織, “観光スポット推薦アプリ「京のおすすめ」を用いた長期実証実験”, 観光と情報, Vol. 10, No. 1, pp. 15-24, 2014.PDF
  • M. Dong, T. Kimata, K. Sugiura and K. Zettsu, “Quality-of-Experience (QoE) in Emerging Mobile Social Networks,” IEICE Transactions on Information and Systems, Vol.E97-D, No.10, pp. 2606-2612, 2014.PDF
  • 稲邑哲也, タンジェフリートゥチュアン, 萩原良信, 杉浦孔明, 長井隆行, 岡田浩之, “大規模長時間のインタラクションを可能にするロボカップ＠ホームシミュレーションの構想とその基盤技術”, 日本知能情報ファジィ学会誌, Vol.26, No.3, pp. 698-709, 2014.PDF
  • 杉浦孔明, 長井隆行, “ロボカップ＠ホームにおける日用品マニピュレーション”, 日本ロボット学会誌, Vol. 31, No. 4, pp. 370-375, 2013.PDF
  • 杉浦孔明, “ロボット対話 -実世界情報を用いたコミュニケーションの学習-“, 人工知能学会誌, Vol. 27 No. 6, pp. 580-586, 2012.
  • 柏岡秀紀, 翠輝久, 水上悦雄, 杉浦孔明, 岩橋直人, 堀智織, “観光案内への音声対話システムの活用”, 情報処理学会デジタルプラクティス, Vol. 3, No. 4, pp. 254-261, 2012.PDF
  • 杉浦孔明, “ロボカップ道しるべ第８回「ロボカップ＠ホームリーグ」”, 情報処理, Vol. 53, No. 3, pp. 250-261, 2012.PDF
  • 中村友昭, アッタミミムハンマド, 杉浦孔明, 長井隆行, 岩橋直人, 戸田智基, 岡田浩之, 大森隆司, “拡張モバイルマニピュレーションのための新規物体の学習”, 日本ロボット学会誌, Vol.30, No.2, pp. 213-224, 2012.
  • T. Nakamura, K. Sugiura, T. Nagai, N. Iwahashi, T. Toda, H. Okada, T. Omori, “Learning Novel Objects for Extended Mobile Manipulation”, Journal of Intelligent and Robotic Systems, Vol. 66, Issue 1-2 , pp 187-204. 2012.PDF
  • K. Sugiura, N. Iwahashi, H. Kawai, S. Nakamura, “Situated Spoken Dialogue with Robots Using Active Learning”, Advanced Robotics, Vol.25, No.17, pp. 2207-2232, 2011.PDF
  • T. Misu, K. Sugiura, T. Kawahara, K. Ohtake, C. Hori, H. Kashioka, H. Kawai and S. Nakamura, “Modeling Spoken Decision Support Dialogue and Optimization of its Dialogue Strategy”, ACM Transactions on Speech and Language Processing, Vol. 7, Issue 3, pp.10:1-10:18, 2011.
  • K. Sugiura, N. Iwahashi, H. Kashioka, and S. Nakamura, “Learning, Generation, and Recognition of Motions by Reference-Point-Dependent Probabilistic Models”, Advanced Robotics, Vol. 25, No. 6-7, pp. 825-848, 2011.PDF
  • X. Zuo, N. Iwahashi, K. Funakoshi, M. Nakano, R. Taguchi, S. Matsuda, K. Sugiura, and N. Oka, “Detecting Robot-Directed Speech by Situated Understanding in Physical Interaction”, Journal of the Japanese Society for Artificial Intelligence, Vol.25, No.6, pp. 670-682, 2010.PDF
  • 杉浦孔明, 岩橋直人, 柏岡秀紀, 中村哲, “言語獲得ロボットによる発話理解確率の推定に基づく物体操作対話”, 日本ロボット学会誌, Vol. 28, No. 8, pp. 978-988, 2010.PDF
  • K. Sugiura, H. Kawakami, and O. Katai, “Simultaneous Design Method of the Sensory Morphology and Controller of Mobile Robots”, Electrical Engineering in Japan, Vol. 172, Issue 1, pp 48-57, 2010.
  • T. Taniguchi, N. Iwahashi, K. Sugiura, and T. Sawaragi, “Constructive Approach to Role-Reversal Imitation Through Unsegmented Interactions”, Journal of Robotics and Mechatronics, Vol.20, No.4, pp. 567-577, 2008.
  • 杉浦孔明，川上浩司，片井修, “移動ロボットにおけるセンサ形態と制御系の同時設計法”, 電気学会論文誌C, Vol. 128-C, No. 7, pp. 1154-1161, 2008.PDF
  • K. Sugiura, T. Shiose, H. Kawakami, and O. Katai, “Co-evolution of Sensors and Controllers”, IEEJ Trans. EIS, Vol. 124-C, pp. 1938-1943, 2004.

International Conferences

  • N. Hosomi, Y. Iioka, S. Hatanaka, T. Misu, K. Yamada, and K. Sugiura: “Target Position Regression from Navigation Instructions”, IEEE ICRA, 2024 [poster].
  • R. Korekata, K. Kanda, S. Nagashima, Y. Imai, and K. Sugiura: “Multimodal Ranking for Target Objects and Receptacles Based on Open-Vocabulary Instructions”, IEEE ICRA, 2024 [poster].
  • Y. Wada, K. Kaneda, D. Saito, and K. Sugiura, “Polos: Multimodal Metric Learning from Human Feedback for Image Captioning”, CVPR, 2024, to appear.
  • Y. Wada, K. Kaneda, and K. Sugiura, “JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning Models”, CoNLL, 2023. (acceptance rate = 28%) PDF
  • Y. Iioka, Y. Yoshida, Y. Wada, S. Hatanaka, and K. Sugiura, “Multimodal Diffusion Segmentation Model for Object Segmentation from Manipulation Instructions”, IEEE/RSJ IROS, pp. 7590-7597, 2023. PDF
  • S. Otsuki, S. Ishikawa, and K. Sugiura, “Prototypical Contrastive Transfer Learning for Multimodal Language Understanding”, IEEE/RSJ IROS, pp. 25-32, 2023. PDF
  • R. Korekata, M. Kambara, Y. Yoshida, S. Ishikawa, Y. Kawasaki, M. Takahashi, and K. Sugiura, “Switching Head–Tail Funnel UNITER for Dual Referring Expression Comprehension with Fetch-and-Carry Tasks”, IEEE/RSJ IROS, pp. 3865-3872, 2023. PDF
  • K. Kaneda, R. Korekata, Y. Wada, S. Nagashima, M. Kambara, Y. Iioka, H. Matsuo, Y. Imai, T. Nishimura, and K. Sugiura, “DialMAT: Dialogue-Enabled Transformer with Moment-Based Adversarial Training”, CVPR 2023 Embodied AI Workshop, 2023.PDF
  • M. Kambara and K. Sugiura, “Fully Automated Task Management for Generation, Execution, and Evaluation: A Framework for Fetch-and-Carry Tasks with Natural Language Instructions in Continuous Space”, CVPR 2023 Embodied AI Workshop, 2023.PDF
  • K. Kaneda, Y. Wada, T. Iida, N. Nishizuka, Y. Kubo, K. Sugiura: “Flare Transformer: Solar Flare Prediction using Magnetograms and Sunspot Physical Features”, ACCV, pp. 1488-1503, 2022. (acceptance rate = 33.4%) PDF
  • T. Iida, T. Komatsu, K. Kaneda, T. Hirakawa, T. Yamashita, H. Fujiyoshi, K. Sugiura: “Visual Explanation Generation Based on Lambda Attention Branch Networks”, ACCV, pp. 3536-3551, 2022. (acceptance rate = 33.4%) PDF
  • H. Matsuo, S. Hatanaka, A. Ueda, T. Hirakawa, T. Yamashita, H. Fujiyoshi, K. Sugiura: “Collision Prediction and Visual Explanation Generation Using Structural Knowledge in Object Placement Tasks”, IEEE/RSJ IROS, 2022 [poster].
  • R. Korekata, Y. Yoshida, S. Ishikawa, K. Sugiura: “Switching Funnel UNITER: Multimodal Instruction Comprehension for Object Manipulation Tasks”, IEEE/RSJ IROS, 2022 [poster].
  • M. Kambara, K.Sugiura, “Relational Future Captioning Model for Explaining Likely Collisions in Daily Tasks”, IEEE ICIP, TP-V2.V13.14, 2022.PDF
  • S. Ishikawa, K. Sugiura, “Moment-based Adversarial Training for Embodied Language Comprehension”, IEEE ICPR, 523, 2022.PDF
  • T. Matsubara, S.Otsuki, Y. Wada, H. Matsuo, T. Komatsu, Y. Iioka, K. Sugiura, H. Saito, “Shared Transformer Encoder with Mask-based 3D Model Estimation for Container Mass Estimation”, IEEE ICASSP, pp.9142–9146, 2022.PDF
  • S. Matsumori, K. Shingyouchi, Y. Abe, Y. Fukuchi, K. Sugiura, M. Imai, “Unified Questioner Transformer for Descriptive Question Generation in Goal-Oriented Visual Dialogue”, IEEE ICCV, pp. 1898-1907, 2021. (acceptance rate = 25.9%) PDF
  • M. Kambara and K. Sugiura, “Case Relation Transformer: A Crossmodal Language Generation Model for Fetching Instructions”, IEEE RAL presented at IEEE/RSJ IROS, 2021.PDF
  • S. Ishikawa and K. Sugiura, “Target-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots”, IEEE RAL presented at IEEE/RSJ IROS, 2021.PDF
  • A. Magassouba, K. Sugiura, and H. Kawai, “CrossMap Transformer: A Crossmodal Masked Path Transformer Using Double Back-Translation for Vision-and-Language Navigation”, IEEE RAL presented at IEEE/RSJ IROS, 2021.PDF
  • H. Itaya, T. Hirakawa, T. Yamashita, H. Fujiyoshi and K. Sugiura, “Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning”, IEEE IJCNN, 2021.PDF
  • T. Ogura, A. Magassouba, K. Sugiura, T. Hirakawa, T. Yamashita, H. Fujiyoshi, H. Kawai, “Alleviating the Burden of Labeling: Sentence Generation by Attention Branch Encoder-Decoder Network”, IEEE RAL presented at IEEE/RSJ IROS, 2020.PDF
  • P. Shen, X. Lu, K. Sugiura, S. Li, H. Kawai, “Compensation on x-vector for Short Utterance Spoken Language Identification”, Odyssey 2020 The Speaker and Language Recognition Workshop, pp. 47-52, Tokyo, Japan, 2020.PDF
  • A. Magassouba, K. Sugiura, H. Kawai, “A Multimodal Target-Source Classifier with Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects”, IEEE RAL presented at IEEE ICRA, 2020.PDF
  • A. Magassouba, K. Sugiura, A. Trinh Quoc, H. Kawai, “Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification”, IEEE Robotics and Automation Letters presented at IEEE/RSJ IROS, Macau, China, 2019.PDF
  • A. Magassouba, K. Sugiura, H. Kawai, “Multimodal Attention Branch Network for Perspective-Free Sentence Generation”, Conference on Robot Learning (CoRL), Osaka, Japan, 2019. (acceptance rate = 27.6%) PDF
  • A. Nakayama, A. Magassouba, K. Sugiura, H. Kawai: “PonNet: Object Placeability Classifier for Domestic Service Robots,” Third International Workshop on Symbolic-Neural Learning (SNL-2019), Tokyo, Japan, July 11-12, 2019 [poster].
  • A. Magassouba, K. Sugiura, H. Kawai, “A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions”, IEEE Robotics and Automation Letters presented at IEEE/RSJ IROS, Madrid, Spain, 2018. IROS 2018 RoboCup Best Paper AwardPDFSlides
  • K. Sugiura, “SuMo-SS: Submodular Optimization Sensor Scattering for Deploying Sensor Networks by Drones”, IEEE Robotics and Automation Letters presented at IEEE/RSJ IROS, Madrid, Spain, 2018.PDFSlides
  • N. Nishizuka, K. Sugiura, Y. Kubo, M. Den, S. Watari and M. Ishii, “Solar Flare Prediction Using Machine Learning with Multiwavelength Observations”, In Proc. IAU Symposium 335, Exeter, UK, vol.13, pp.310-313, 2018.
  • K. Sugiura and H. Kawai, “Grounded Language Understanding for Manipulation Instructions Using GAN-Based Classification”, In Proc. IEEE ASRU, Okinawa, Japan, pp. 519-524, 2017.PDF
  • K. Sugiura and K. Zettsu, “Analysis of Long-Term and Large-Scale Experiments on Robot Dialogues Using a Cloud Robotics Platform”, In Proc. ACM/IEEE HRI, Christchurch, New Zealand, pp. 525-526, 2016.PDF
  • S. Takeuchi, K. Sugiura, Y. Akahoshi, and K. Zettsu, “Constrained Region Selection Method Based on Configuration Space for Visualization in Scientific Dataset Search,” In Proc. IEEE Big Data, vol. 2, pp. 2191-2200, 2015.PDF
  • K. Sugiura and K. Zettsu, “Rospeex: A Cloud Robotics Platform for Human-Robot Spoken Dialogues”, In Proc. IEEE/RSJ IROS, pp. 6155-6160, Hamburg, Germany, Oct 1, 2015.PDF
  • T. Nose, Y. Arao, T. Kobayashi, K. Sugiura, Y. Shiga, and A. Ito, “Entropy-Based Sentence Selection for Speech Synthesis Using Phonetic and Prosodic Contexts”, In Proc. Interspeech, pp. 3491-3495, Dresden, Germany, Sep. 2015.PDF
  • K. Lwin, K. Zettsu, and K. Sugiura, “Geovisualization and Correlation Analysis between Geotagged Twitter and JMA Rainfall Data: Case of Heavy Rain Disaster in Hiroshima”, In Proc. Second IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Fuzhou, China, July 2015.PDF
  • B. T. Ong, K. Sugiura, and K. Zettsu, “Dynamic Pre-training of Deep Recurrent Neural Networks for Predicting Environmental Monitoring Data,” In Proc. IEEE BigData 2014, pp. 760-765, Washington DC, USA, Oct 30, 2014. (acceptance rate = 18.5%) PDF
  • B. T. Ong, K. Sugiura, and K. Zettsu, “Predicting PM2.5 Concentrations Using Deep Recurrent Neural Networks with Open Data,” In Proc. iDB Workshop 2014, Fukuoka, Japan, July 31, 2014.
  • D. Holz, J. Ruiz-del-Solar, K. Sugiura, S. Wachsmuth, “On RoboCup@Home – Past, Present and Future of a Scientific Competition for Service Robots”, In Proc. RoboCup Symposium, pp. 686-697, Joao Pessoa, Brazil, July 25, 2014.
  • D. Holz, L. Iocchi, J. Ruiz-del-Solar, K. Sugiura, and T. van der Zant, “RoboCup@Home | a competition as a testbed for domestic service robots,” In Proc. 1st International Workshop on Intelligent Robot Assistants, Padova, Italy, July 15, 2014.
  • S. Takeuchi, Y. Akahoshi, B. T. Ong, K. Sugiura, and K. Zettsu, “Spatio-Temporal Pseudo Relevance Feedback for Large-Scale and Heterogeneous Scientific Repositories,” In Proc. 2014 IEEE International Congress on Big Data, pp. 669-676, Anchorage, USA, July 1, 2014.PDF
  • K. Sugiura, Y. Shiga, H. Kawai, T. Misu and C. Hori, “Non-Monologue HMM-Based Speech Synthesis for Service Robots: A Cloud Robotics Approach,” In Proc. IEEE ICRA, pp.2237-2242. Hong Kong, China, June 3, 2014.PDF
  • J. Tan, T. Inamura, K. Sugiura, T. Nagai, and H. Okada, “Human-Robot Interaction between Virtual and Real Worlds: Motivation from RoboCup@Home,” In Proc. International Conference on Social Robotics, pp.239-248, Bristol, UK, Oct 27, 2013.
  • T. Inamura, J. Tan, K. Sugiura, T. Nagai, and H. Okada, “Development of RoboCup@Home Simulation towards Long-term Large Scale HRI,” In Proc. RoboCup Symposium, Eindhoven, The Netherlands, July 1, 2013.
  • R. Lee, K. Kim, K. Sugiura, K. Zettsu, Y. Kidawara, “Complementary Integration of Heterogeneous Crowd-sourced Datasets for Enhanced Social Analytics,” In Proc. IEEE MDM, vol. 2, pp. 234-243, Milan, Italy, June 3, 2013.PDF
  • K. Sugiura, R. Lee, H. Kashioka, K. Zettsu, and Y. Kidawara, “Utterance Classification Using Linguistic and Non-Linguistic Information for Network-Based Speech-To-Speech Translation Systems,” In Proc. IEEE MDM, vol. 2, pp. 212-216, Milan, Italy, June 3, 2013.PDF
  • K. Sugiura, Y. Shiga, H. Kawai, T. Misu and C. Hori, “Non-Monologue Speech Synthesis for Service Robots,” In Proc. Fifth Workshop on Gaze in HRI, Tokyo, Japan, March 3, 2013.
  • K. Sugiura, N. Iwahashi and H. Kashioka, “Motion Generation by Reference-Point-Dependent Trajectory HMMs,” In Proc. IEEE/RSJ IROS, pp.350-356, San Francisco, USA, September 25-30, 2011. 【IROS 2011 RoboCup Best Paper Award受賞】PDF
  • T. Misu, K. Sugiura, K. Ohtake, C. Hori, H. Kashioka, H. Kawai and S. Nakamura, “Modeling Spoken Decision Making Dialogue and Optimization of its Dialogue Strategy”, In Proc. SIGDIAL, pp.221-224, 2011.
  • T. Misu, K. Sugiura, K. Ohtake, C. Hori, H. Kashioka, H. Kawai and S. Nakamura, “Dialogue Strategy Optimization to Assist User’s Decision for Spoken Consulting Dialogue Systems”, In Proc. IEEE-SLT, pp.342-347, 2010.PDF
  • N. Iwahashi, K. Sugiura, R. Taguchi, T. Nagai, and T. Taniguchi, “Robots That Learn to Communicate: A Developmental Approach to Personally and Physically Situated Human-Robot Conversations”, In Proc. The 2010 AAAI Fall Symposium on Dialog with Robots, pp. 38-43, Arlington, Virginia, USA, November 11-13, 2010.PDF
  • K. Sugiura, N. Iwahashi, H. Kawai, and S. Nakamura, “Active Learning for Generating Motion and Utterances in Object Manipulation Dialogue Tasks”, In Proc. The 2010 AAAI Fall Symposium on Dialog with Robots, pp. 115-120, Arlington, Virginia, USA, November 11-13, 2010.PDF
  • K. Sugiura, N. Iwahashi, H. Kashioka, and S. Nakamura, “Active Learning of Confidence Measure Function in Robot Language Acquisition Framework”, In Proc. IEEE/RSJ IROS, pp. 1774-1779, Taipei, Taiwan, Oct 18-22, 2010.PDF
  • X. Zuo, N. Iwahashi, R. Taguchi, S. Matsuda, K. Sugiura, K. Funakoshi, M. Nakano, and N. Oka, “Detecting Robot-Directed Speech by Situated Understanding in Physical Interaction”, In Proc. IEEE RO-MAN, pp. 643-648, 2010.PDF
  • M. Attamimi, A. Mizutani, T. Nakamura, K. Sugiura, T. Nagai, N. Iwahashi, H. Okada, and T. Omori, “Learning Novel Objects Using Out-of-Vocabulary Word Segmentation and Object Extraction for Home Assistant Robots”, In Proc. IEEE ICRA, pp. 745-750, Anchorage, Alaska, USA, May 3-8, 2010. 【2011年 ロボカップ研究賞受賞（ロボカップ日本委員会）】PDF
  • X. Zuo, N. Iwahashi, R. Taguchi, S. Matsuda, K. Sugiura, K. Funakoshi, M. Nakano, and N. Oka, “Robot-Directed Speech Detection Using Multimodal Semantic Confidence Based on Speech, Image, and Motion”, In Proc. IEEE ICASSP, pp. 2458-2461, Dallas, Texas, USA, March 14-19, 2010.PDF
  • T. Misu, K. Sugiura, T. Kawahara, K. Ohtake, C. Hori, H. Kashioka, and S. Nakamura, “Online Learning of Bayes Risk-Based Optimization of Dialogue Management for Document Retrieval Systems with Speech Interface”, In Proc. IWSDS, 2009.
  • K. Sugiura, N. Iwahashi, H. Kashioka, and S. Nakamura, “Bayesian Learning of Confidence Measure Function for Generation of Utterances and Motions in Object Manipulation Dialogue Task”, In Proc. Interspeech, pp. 2483-2486, Brighton, UK, September, 2009.PDF
  • N. Iwahashi, R. Taguchi, K. Sugiura, K. Funakoshi, and M. Nakano, “Robots that Learn to Converse: Developmental Approach to Situated Language Processing”, In Proc. International Symposium on Speech and Language Processing, pp. 532-537, China, August, 2009.
  • K. Sugiura and N. Iwahashi, “Motion Recognition and Generation by Combining Reference-Point-Dependent Probabilistic Models”, In Proc. IEEE/RSJ IROS, pp. 852-857, Nice, France, September, 2008.PDF
  • K. Sugiura and N. Iwahashi, “Learning Object-Manipulation Verbs for Human-Robot Communication”, In Proc. Workshop on Multimodal Interfaces in Semantic Interaction, pp. 32-38, Nagoya, Japan, November, 2007.PDF
  • K. Sugiura, T. Nishikawa, M. Akahane, and O. Katai: “Autonomous Design of a Line-Following Robot by Exploiting Interaction between Sensory Morphology and Learning Controller”, In Proc. the 2nd Biomimetics International Conference, Doshisha, pp. 23-24, Kyoto, Japan, December, 2006
  • K. Sugiura, D. Matsubara, and O. Katai: “Construction of Robotic Body Schema by Extracting Temporal Information from Sensory Inputs”, In Proc. SICE-ICASE, pp. 302-307, Busan, Korea, October, 2006.PDF
  • M. Akahane, K. Sugiura, T. Shiose, H. Kawakami, and O. Katai: “Autonomous Design of Robot Morphology for Learning Behavior Using Evolutionary Computation”, In Proc. 2005 Japan-Australia Workshop on Intelligent and Evolutionary Systems, Hakodate, Japan, CD-ROM, 2005.
  • K. Sugiura, M. Akahane, T. Shiose, K. Shimohara, and O. Katai: “Exploiting Interaction between Sensory Morphology and Learning”, In Proc. IEEE-SMC, Hawaii, USA, pp. 883-888, 2005.PDF
  • K. Sugiura, T. Shiose, H. Kawakami, and O. Katai: “Co-evolution of Sensors and Controllers”, In Proc. 2003 Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2003), Kitakyushu, Japan, pp. 145-150, 2003.PDF
  • K. Sugiura, H. Suzuki, T. Shiose, H. Kawakami, and O. Katai: “Evolution of Rewriting Rule Sets Using String-Based Tierra”, In Proc. ECAL, Dortmund, Germany, pp. 69-77, 2003.PDF

Awards

  • S. Nagashima, R. Korekata, K. Kaneda, K. Sugiura, Toyota Motor Corporation HSR Community Best Paper Award, The 41st Annual Conference of the Robotics Society of Japan, 12 September 2023.
  • K. Kaneda, R. Korekata, Y. Wada, S. Nagashima, M. Kambara, Y. Iioka, H. Matsuo, Y. Imai, T. Nishimura, K. Sugiura, 1st Place in CVPR 2023 Embodied AI Workshop DialFRED Challenge, 19 June 2023.
  • M. Kambara, Y. Yoshida, K. Kaneda, S. Otsuki, R. Korekata, H. Matsuo, Y. Wada, W. Yang, K. Sugiura, Honorable Mention Award, REVERIE Challenge @ CSIG 2022, 19 August 2022.
  • T. Matsubara, S.Otsuki, Y. Wada, H. Matsuo, T. Komatsu, Y. Iioka, K. Sugiura, H. Saito, Best performing solution for container capacity estimation and capacity and dimensions estimation and filling mass estimation, The CORSMAL challenge 2022, 23 June 2022.
  • HSR Community Best Presentation Award, Toyota Motor Corporation HSR Commuity General Assembly 2021, 24 March 2022.
  • Best Resarch Award, Toyota Motor Corporation HSR Community General Assembly 2020, 23 November 2020.
  • METI Minister’s Award (1st Place) in WRS2018 Partner Robot Challenge / Virtual Space, 21 October 2018.
  • Japanese Society for Artificial Intelligence Award in WRS 2018, 21 October 2018.
  • A. Magassouba, K. Sugiura, H. Kawai, IEEE/RSJ IROS 2018 RoboCup Best Paper Award, 4 October 2018.
  • K. Sugiura, A. Magassouba, JSAI2018 Best Paper Award, 26 July 2018.
  • 3rd Place in RoboCup 2018 RoboCup@Home League Domestic Standard Platform, 21 June 2018.
  • 2nd Place in WRS Partner Robot Challenge (Virtual Space) Pre-event 2018, 5 May 2018.
  • 2nd Place in RoboCup 2017 RoboCup@Home League Domestic Standard Platform, 30 July 2017.
  • Open Source Software Award, RoboCup 2017 @Home League, 30 July 2017.
  • Outstanding Achievement Award, Toyota Motor Corporation HSR Community General Assembly 2017, 28 February 2017.
  • Innovation Award, RoboCup 2016 @Home League, 3 July 2016.
  • 1st Place, Toyota HSR Hackathon 2015, 2 September 2015.
  • Best Presentation, NICT Joint Research Workshop, 28 July 2014.
  • 2nd Place in RoboCup 2012 @Home League, 23 June 2012.
  • 1st Place in RoboCup 2012 Japan Open @Home League, 5 May 2012.
  • K. Sugiura, N. Iwahashi, H. Kashioka, IROS 2011 RoboCup Best Paper Award, 29 September 2011.
  • The Japanese Society for Artificial Intelligence Award in RoboCup 2011 Japan Open, 5 May 2011.
  • 1st Place in RoboCup 2011 Japan Open @Home League, 5 May 2011.
  • M. Attamimi, A. Mizutani, T. Nakamura, K. Sugiura, T. Nagai, N. Iwahashi, H. Okada, T. Omori, RoboCup Research Award, The RoboCup Japanese National Committee, 3 May 2011.
  • 1st Place in RoboCup 2010 @Home League, 24 June 2010.
  • The Robotics Society of Japan Award in RoboCup 2010 Japan Open, 4 May 2010.
  • 1st Place in RoboCup 2010 Japan Open @Home League, 4 May 2010.
  • 2nd Place in RoboCup 2009 @Home League, 5 July 2009.
  • The Japanese Society for Artificial Intelligence Award in RoboCup 2009 Japan Open, 10 May 2009.
  • 1st Place in RoboCup 2009 Japan Open @Home League, 10 May 2009.
  • K. Sugiura, Young Researcher Award of Electronics, Information and Systems Society, The Institute of Electrical Engineers of Japan, 8 August 2008.
  • 1st Place in RoboCup 2008 @Home League, July 2008.
  • 1st Place in RoboCup 2008 Japan Open @Home League, May 2008.

Book Chapters

  • A. Magassouba, K. Sugiura, and H. Kawai: “Latent-Space Data Augmentation for Visually-Grounded Language Understanding”, Advances in Artificial Intelligence (ISBN 978-3-030-39877-4), Ohsawa, Y., Yada, K., Ito, T., Takama, Y., Sato-Shimokawara, E., Abe, A., Mori, J., Matsumura, N. (Eds.), Springer, Vol. 1128 AISC, pp. 179-187, 2020.Download
  • アンジェロ カンジェロシ, マシュー シュレシンジャー(著), 岡田浩之,谷口忠大,萩原良信,荒川直哉,長井隆行,尾形哲也,稲邑哲也,岩橋直人,杉浦孔明,牧野武文(訳): “発達ロボティクスハンドブック ロボットで探る認知発達の仕組み”, 2019.
  • 人工知能学会(編), 人工知能学大事典, 「模倣学習」, 共立出版, pp. 1039–1041, 2017.
  • K. Sugiura, S. Behnke, D. Kulic, and K. Yamazaki (eds): “Special Issue on Machine Learning and Data Engineering in Robotics”, Advanced Robotics, Vol. 30, Issue 11-12, May 10, 2016.PDF
  • R. A. C. Bianchi, H. Levent Akin, S. Ramamoorthy, and K. Sugiura (eds): “RoboCup 2014: Robot World Cup XVIII”, Lecture Notes in Computer Science 8992 (ISBN 978-3-319-18614-6), Springer, July 15, 2014.
  • M. Attamimi, T. Nakamura, K. Sugiura, T. Nagai, and N. Iwahashi, “Learning Novel Objects for Domestic Service Robots”, The Future of Humanoid Robots: Research and Applications (ISBN 978-953-307-951-6), InTech, pp. 257-276, 2012.
  • T. Misu, K. Sugiura, T. Kawahara, K. Ohtake, C. Hori, H. Kashioka and S. Nakamura: “Online learning of Bayes Risk-based Optimization of Dialogue Management for Document Retrieval Systems with Speech Interface (Chapter 2)”, Spoken Dialogue Systems Technology and Design (ISBN 978-1441979339), Springer, pp. 29-62, 2010.
  • K. Sugiura, N. Iwahashi, H. Kashioka, and S. Nakamura: “Statistical Imitation Learning in Sequential Object Manipulation Tasks”, Advances in Robot Manipulators, Ernest Hall (Ed.), InTech, pp. 589-606, 2010.Download

Domestic Conferences

  • Full list is shown here.

Patents

  • Full list is shown here.

Theses

  • Full list is shown here.