尾形 哲也

研究成果

年別の研究成果 1996 2005 2006 2007 2008 2009 2010 2011 2012 2018 2019 2022 2023

• 216 Conference contribution
• 84 Article
• 21 Conference article
• 18 Paper
• 11 その他
  • 8 Editorial
  • 2 Chapter
  • 1 Letter

年別の研究成果

年別の研究成果

検索結果

• 2023

  Learning-based collision-free planning on arbitrary optimization criteria in the latent space through cGANs

  Ando, T., Iino, H., Mori, H., Torishima, R., Takahashi, K., Yamaguchi, S., Okanohara, D. & Ogata, T., 2023, In: Advanced Robotics. 37, 10, p. 621-633 13 p.

  研究成果: Article › 査読

  • Trajectories 100%
  • Planning 91%
  • Robots 69%
  • Robotic arms 42%

• Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions

  Yasutomi, A. Y., Ichiwara, H., Ito, H., Mori, H. & Ogata, T., 2023 3月 1, In: IEEE Robotics and Automation Letters. 8, 3, p. 1834-1841 8 p.

  研究成果: Article › 査読

  • Reinforcement Learning 100%
  • Data-driven 75%
  • Vision 68%
  • Reinforcement learning 66%
  • Lighting 44%
• 2022

  Deep Active Visual Attention for Real-Time Robot Motion Generation: Emergence of Tool-Body Assimilation and Adaptive Tool-Use

  Hiruma, H., Ito, H., Mori, H. & Ogata, T., 2022 7月 1, In: IEEE Robotics and Automation Letters. 7, 3, p. 8550-8557 8 p.

  研究成果: Article › 査読

  • Visual Attention 100%
  • Robot 65%
  • Real-time 60%
  • Motion 38%
  • Robots 34%
  1 被引用数 (Scopus)

• Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control

  Ito, H., Yamamoto, K., Mori, H. & Ogata, T., 2022 4月 1, In: Science Robotics. 7, 65, eaax8177.

  研究成果: Article › 査読

  • Multi-task Learning 100%
  • Predictive Model 80%
  • Multi-task learning 78%
  • Robot 57%
  • Learning 43%
  7 被引用数 (Scopus)

• Emergence of sensory attenuation based upon the free-energy principle

  Idei, H., Ohata, W., Yamashita, Y., Ogata, T. & Tani, J., 2022 12月, In: Scientific reports. 12, 1, 14542.

  研究成果: Article › 査読

  Open Access

  • Learning 100%
  • Computer Neural Networks 88%
  • Executive Function 70%
  • Brain 33%
  3 被引用数 (Scopus)

• Learning Bidirectional Translation Between Descriptions and Actions With Small Paired Data

  Toyoda, M., Suzuki, K., Hayashi, Y. & Ogata, T., 2022 10月 1, In: IEEE Robotics and Automation Letters. 7, 4, p. 10930-10937 8 p.

  研究成果: Article › 査読

  • Paired Data 100%
  • Large dataset 75%
  • Learning 62%
  • Visualization 53%
  • Robots 44%

• Multi-Fingered In-Hand Manipulation With Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors

  Funabashi, S., Isobe, T., Hongyi, F., Hiramoto, A., Schmitz, A., Sugano, S. & Ogata, T., 2022 4月 1, In: IEEE Robotics and Automation Letters. 7, 2, p. 2102-2109 8 p.

  研究成果: Article › 査読

  • Tactile Sensor 100%
  • Distributed Sensor 84%
  • Manipulation 47%
  • Object 30%
  • Labels 25%
  4 被引用数 (Scopus)

• Robot Task Learning with Motor Babbling Using Pseudo Rehearsal

  Kase, K., Tateishi, A. & Ogata, T., 2022 7月 1, In: IEEE Robotics and Automation Letters. 7, 3, p. 8377-8382 6 p.

  研究成果: Article › 査読

  • Robot 100%
  • Learning 74%
  • Robots 52%
  • Demonstrations 36%
  • Skills 31%

• Tactile Transfer Learning and Object Recognition With a Multifingered Hand Using Morphology Specific Convolutional Neural Networks

  Funabashi, S., Yan, G., Hongyi, F., Schmitz, A., Jamone, L., Ogata, T. & Sugano, S., 2022, (Accepted/In press) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-15 15 p.

  研究成果: Article › 査読

  • Transfer learning 100%
  • Machine Learning 95%
  • Object recognition 87%
  • Touch 84%
  • Convolutional neural networks 76%
  1 被引用数 (Scopus)

• Utilization of Image/Force/Tactile Sensor Data for Object-Shape-Oriented Manipulation: Wiping Objects with Turning Back Motions and Occlusion

  Saito, N., Shimizu, T., Ogata, T. & Sugano, S., 2022 4月 1, In: IEEE Robotics and Automation Letters. 7, 2, p. 968-975 8 p.

  研究成果: Article › 査読

  • Tactile Sensor 100%
  • Force Sensor 96%
  • Occlusion 67%
  • Manipulation 47%
  • Robot 46%
  2 被引用数 (Scopus)
• 2021

  Compensation for Undefined Behaviors during Robot Task Execution by Switching Controllers Depending on Embedded Dynamics in RNN

  Suzuki, K., Mori, H. & Ogata, T., 2021 4月, In: IEEE Robotics and Automation Letters. 6, 2, p. 3475-3482 8 p., 9368970.

  研究成果: Article › 査読

  • Robot 100%
  • Controller 77%
  • Compensation and Redress 62%
  • Robots 52%
  • Controllers 43%
  9 被引用数 (Scopus)

• Development of a basic educational kit for robotic system with deep neural networks

  Kanamura, M., Suzuki, K., Suga, Y. & Ogata, T., 2021 6月 1, In: Sensors. 21, 11, 3804.

  研究成果: Article › 査読

  Open Access

  • kits 100%
  • Robotics 86%
  • robotics 83%
  • Deep neural networks 68%
  • machine learning 29%
  3 被引用数 (Scopus)

• Embodying Pre-Trained Word Embeddings through Robot Actions

  Toyoda, M., Suzuki, K., Mori, H., Hayashi, Y. & Ogata, T., 2021 4月, In: IEEE Robotics and Automation Letters. 6, 2, p. 4225-4232 8 p., 9384172.

  研究成果: Article › 査読

  • Robot 100%
  • Robots 52%
  • Linguistics 38%
  • Transform 17%
  • Dialogue 16%
  5 被引用数 (Scopus)

• How to Select and Use Tools? Active Perception of Target Objects Using Multimodal Deep Learning

  Saito, N., Ogata, T., Funabashi, S., Mori, H. & Sugano, S., 2021 4月, In: IEEE Robotics and Automation Letters. 6, 2, p. 2517-2524 8 p., 9362222.

  研究成果: Article › 査読

  • Perception 100%
  • Learning 73%
  • Deep learning 72%
  • Target 69%
  • Robot 66%
  14 被引用数 (Scopus)

• Leveraging motor babbling for efficient robot learning

  Kase, K., Matsumoto, N. & Ogata, T., 2021 10月, In: Journal of Robotics and Mechatronics. 33, 5, p. 1063-1074 12 p.

  研究成果: Article › 査読

  Open Access

  • Robot learning 100%
  • Demonstrations 56%
  • Robots 37%
  • Deep learning 8%
  • Tuning 7%
  1 被引用数 (Scopus)

• Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder

  Idei, H., Murata, S., Yamashita, Y. & Ogata, T., 2021 6月, In: Neural Networks. 138, p. 150-163 14 p.

  研究成果: Article › 査読

  Open Access

  • Neurodevelopmental Disorders 100%
  • Robots 54%
  • Learning 46%
  • Autism Spectrum Disorder 44%
  • Recurrent neural networks 44%
  3 被引用数 (Scopus)

• Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks

  Saito, N., Ogata, T., Mori, H., Murata, S. & Sugano, S., 2021 9月 28, In: Frontiers in Robotics and AI. 8, 748716.

  研究成果: Article › 査読

  Open Access

  • Deep neural networks 100%
  • Robots 39%
  1 被引用数 (Scopus)
• 2020

  Evaluation of Generalization Performance of Visuo-Motor Learning by Analyzing Internal State Structured from Robot Motion

  Ito, H., Yamamoto, K., Mori, H. & Ogata, T., 2020 3月 1, In: New Generation Computing. 38, 1, p. 7-22 16 p.

  研究成果: Article › 査読

  • Robot 100%
  • Knobs 92%
  • Learning 74%
  • Internal 67%
  • Evaluation 59%
  3 被引用数 (Scopus)

• Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder

  Idei, H., Murata, S., Yamashita, Y. & Ogata, T., 2020 8月 12, In: Frontiers in Psychiatry. 11, 762.

  研究成果: Article › 査読

  Open Access

  • Neurodevelopmental Disorders 100%
  • Noise 78%
  • Learning 62%
  • Psychological Generalization 28%
  • Autism Spectrum Disorder 22%
  6 被引用数 (Scopus)
• 2019

  Adaptive Drawing Behavior by Visuomotor Learning Using Recurrent Neural Networks

  Sasaki, K. & Ogata, T., 2019 3月, In: IEEE Transactions on Cognitive and Developmental Systems. 11, 1, p. 119-128 10 p., 8453841.

  研究成果: Article › 査読

  Open Access

  • Recurrent neural networks 100%
  • Supervised learning 14%
  • Experiments 4%
  7 被引用数 (Scopus)

• Discontinuous Stabilizing Control of Skid-Steering Mobile Robot (SSMR)

  Ibrahim, F., Abouelsoud, A. A., Fath El Bab, A. M. R. & Ogata, T., 2019 8月 15, In: Journal of Intelligent and Robotic Systems: Theory and Applications. 95, 2, p. 253-266 14 p.

  研究成果: Article › 査読

  • Mobile robots 100%
  • Controllers 60%
  • Asymptotic stability 29%
  • Closed loop systems 25%
  • Fuzzy logic 24%
  5 被引用数 (Scopus)

• Disentanglement in conceptual space during sensorimotor interaction

  Zhong, J., Ogata, T., Cangelosi, A. & Yang, C., 2019 12月, In: Cognitive Computation and Systems. 1, 4, p. 103-112 10 p.

  研究成果: Article › 査読

  Open Access

  • Learning 100%
  • interaction 63%
  • Language Development 57%
  • Names 43%
  • predictive model 42%
  2 被引用数 (Scopus)

• Path following algorithm for skid-steering mobile robot based on adaptive discontinuous posture control

  Ibrahim, F., Abouelsoud, A. A., Fath Elbab, A. M. R. & Ogata, T., 2019 5月 3, In: Advanced Robotics. 33, 9, p. 439-453 15 p.

  研究成果: Article › 査読

  • Mobile robots 100%
  • Landmine detection 84%
  • Trajectories 77%
  • Controllers 60%
  • State feedback 54%
  12 被引用数 (Scopus)

• Sensorimotor input as a language generalisation tool: a neurorobotics model for generation and generalisation of noun-verb combinations with sensorimotor inputs

  Zhong, J., Peniak, M., Tani, J., Ogata, T. & Cangelosi, A., 2019 6月 15, In: Autonomous Robots. 43, 5, p. 1271-1290 20 p.

  研究成果: Article › 査読

  Open Access

  • Anthropomorphic robots 100%
  • Robots 57%
  • Electric grounding 47%
  • Recurrent neural networks 46%
  • Semantics 30%
  10 被引用数 (Scopus)
• 2018

  Acquisition of viewpoint transformation and action mappings via sequence to sequence imitative learning by deep neural networks

  Nakajo, R., Murata, S., Arie, H. & Ogata, T., 2018, In: Frontiers in Neurorobotics. 12, 46.

  研究成果: Article › 査読

  Open Access

  • Deep neural networks 100%
  • Robots 66%
  • Recurrent neural networks 45%
  • Robotics 22%
  • Cameras 10%
  1 被引用数 (Scopus)

• Effective input order of dynamics learning tree

  Kim, C. H., Hama, S., Hirai, R., Takahashi, K., Yamada, H., Ogata, T. & Sugano, S., 2018 2月 1, In: Advanced Robotics. 32, 3, p. 122-136 15 p.

  研究成果: Article › 査読

  • Manipulators 100%
  • Robots 73%
  • Boats 44%
  • Anthropomorphic robots 42%
  • Trajectories 26%
  2 被引用数 (Scopus)

• Encoding Longer-Term Contextual Information with Predictive Coding and Ego-Motion

  Zhong, J., Cangelosi, A., Ogata, T. & Zhang, X., 2018, In: Complexity. 2018, 7609587.

  研究成果: Article › 査読

  Open Access

  • Neural networks 100%
  • Neurons 75%
  • Data storage equipment 50%
  • Experiments 29%
  3 被引用数 (Scopus)

• Learning to Achieve Different Levels of Adaptability for Human-Robot Collaboration Utilizing a Neuro-Dynamical System

  Murata, S., Li, Y., Arie, H., Ogata, T. & Sugano, S., 2018 9月, In: IEEE Transactions on Cognitive and Developmental Systems. 10, 3, p. 712-725 14 p., 8268071.

  研究成果: Article › 査読

  • Dynamical systems 100%
  • Robots 78%
  • Intelligent robots 31%
  • Anthropomorphic robots 27%
  • Recurrent neural networks 25%
  8 被引用数 (Scopus)

• Motion switching with sensory and instruction signals by designing dynamical systems using deep neural network

  Suzuki, K., Mori, H. & Ogata, T., 2018 10月, In: IEEE Robotics and Automation Letters. 3, 4, p. 3481-3488 8 p., 8405582.

  研究成果: Article › 査読

  Open Access

  • Deep neural networks 100%
  • Neural Networks 96%
  • Dynamical systems 84%
  • Dynamical system 76%
  • Motion 74%
  17 被引用数 (Scopus)

• Paired recurrent autoencoders for bidirectional translation between robot actions and linguistic descriptions

  Yamada, T., Matsunaga, H. & Ogata, T., 2018 10月, In: IEEE Robotics and Automation Letters. 3, 4, p. 3441-3448 8 p., 8403309.

  研究成果: Article › 査読

  Open Access

  • Robot 100%
  • Linguistics 90%
  • Vector spaces 56%
  • Robots 52%
  • Deep learning 24%
  33 被引用数 (Scopus)
• 2017

  Dynamic motion learning for multi-DOF flexible-joint robots using active–passive motor babbling through deep learning

  Takahashi, K., Ogata, T., Nakanishi, J., Cheng, G. & Sugano, S., 2017 9月 17, In: Advanced Robotics. 31, 18, p. 1002-1015 14 p.

  研究成果: Article › 査読

  Open Access

  • Deep learning 100%
  • Robots 71%
  • Tuning 21%
  • Degrees of freedom (mechanics) 15%
  • Recurrent neural networks 14%
  12 被引用数 (Scopus)

• Learning to Perceive the World as Probabilistic or Deterministic via Interaction with Others: A Neuro-Robotics Experiment

  Murata, S., Yamashita, Y., Arie, H., Ogata, T., Sugano, S. & Tani, J., 2017 4月, In: IEEE Transactions on Neural Networks and Learning Systems. 28, 4, p. 830-848 19 p.

  研究成果: Article › 査読

  • Robotics 100%
  • Recurrent neural networks 91%
  • Robots 84%
  • Uncertainty 82%
  • Stochastic models 48%
  30 被引用数 (Scopus)

• Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning

  Yang, P. C., Sasaki, K., Suzuki, K., Kase, K., Sugano, S. & Ogata, T., 2017 4月, In: IEEE Robotics and Automation Letters. 2, 2, p. 397-403 7 p., 7762066.

  研究成果: Article › 査読

  Open Access

  • Humanoid Robot 100%
  • Folding 58%
  • Anthropomorphic robots 54%
  • Learning 44%
  • Deep learning 43%
  130 被引用数 (Scopus)

• Representation learning of logic words by an RNN: From word sequences to robot actions

  Yamada, T., Murata, S., Arie, H. & Ogata, T., 2017, In: Frontiers in Neurorobotics. 11, 70.

  研究成果: Article › 査読

  Open Access

  • Robots 100%
  • Long short-term memory 36%
  • Intelligent agents 36%
  • Electric grounding 33%
  • Recurrent neural networks 32%
  10 被引用数 (Scopus)

• Sound source localization using deep learning models

  Yalta, N., Nakadai, K. & Ogata, T., 2017 2月, In: Journal of Robotics and Mechatronics. 29, 1, p. 37-48 12 p.

  研究成果: Article › 査読

  Open Access

  • Image classification 100%
  • Deep neural networks 91%
  • Deep learning 83%
  • Acoustic waves 73%
  • Microphones 49%
  66 被引用数 (Scopus)

• Tool-body assimilation model considering grasping motion through deep learning

  Takahashi, K., Kim, K., Ogata, T. & Sugano, S., 2017 5月 1, In: Robotics and Autonomous Systems. 91, p. 115-127 13 p.

  研究成果: Article › 査読

  • Grasping 100%
  • Robot 63%
  • Learning 57%
  • Deep learning 56%
  • Motion 46%
  35 被引用数 (Scopus)
• 2016

  Dynamical integration of language and behavior in a recurrent neural network for Human-Robot interaction

  Yamada, T., Murata, S., Arie, H. & Ogata, T., 2016, In: Frontiers in Neurorobotics. 10, JUL, 00005.

  研究成果: Article › 査読

  Open Access

  • Human robot interaction 100%
  • Recurrent neural networks 89%
  • Robots 55%
  • Linguistics 16%
  • Switches 12%
  24 被引用数 (Scopus)

• Symbol emergence in robotics: A survey

  Taniguchi, T., Nagai, T., Nakamura, T., Iwahashi, N., Ogata, T. & Asoh, H., 2016 6月 17, In: Advanced Robotics. 30, 11-12, p. 706-728 23 p.

  研究成果: Article › 査読

  • Semiotics 100%
  • Robotics 88%
  • Robots 45%
  • Communication 23%
  • Acoustics 19%
  80 被引用数 (Scopus)

• Visual motor integration of robot's drawing behavior using recurrent neural network

  Sasaki, K., Noda, K. & Ogata, T., 2016 12月 1, In: Robotics and Autonomous Systems. 86, p. 184-195 12 p.

  研究成果: Article › 査読

  • Recurrent Neural Networks 100%
  • Robot 95%
  • Recurrent neural networks 80%
  • Vision 79%
  • Drawing 76%
  24 被引用数 (Scopus)
• 2015

  Audio-visual speech recognition using deep learning

  Noda, K., Yamaguchi, Y., Nakadai, K., Okuno, H. G. & Ogata, T., 2015 6月 1, In: Applied Intelligence. 42, 4, p. 722-737 16 p.

  研究成果: Article › 査読

  Open Access

  • Audiovisual 100%
  • Hidden Markov models 87%
  • Speech recognition 81%
  • Deep learning 77%
  • Convolutional neural networks 52%
  398 被引用数 (Scopus)

• Preferential training of neurodynamical model based on predictability of target dynamics

  Nishide, S., Nobuta, H., Okuno, H. G. & Ogata, T., 2015 5月 3, In: Advanced Robotics. 29, 9, p. 587-596 10 p.

  研究成果: Article › 査読

  • Robots 100%
  • Recurrent neural networks 64%
  • Backpropagation 58%
  • Experiments 16%
  • Learning algorithms 12%
  1 被引用数 (Scopus)

• Tool-body assimilation model based on body babbling and neurodynamical system

  Takahashi, K., Ogata, T., Tjandra, H., Yamaguchi, Y. & Sugano, S., 2015 2月 22, In: Mathematical Problems in Engineering. 2015, 837540.

  研究成果: Article › 査読

  • Model-based 100%
  • Robot 49%
  • Motion 43%
  • Robots 25%
  • Humanoid Robot 20%
  10 被引用数 (Scopus)
• 2014

  Learning to generate proactive and reactive behavior using a dynamic neural network model with time-varying variance prediction mechanism

  Murata, S., Arie, H., Ogata, T., Sugano, S. & Tani, J., 2014 9月 2, In: Advanced Robotics. 28, 17, p. 1189-1203 15 p.

  研究成果: Article › 査読

  • Robots 100%
  • Neural networks 94%
  • Experiments 36%
  9 被引用数 (Scopus)

• Multimodal integration learning of robot behavior using deep neural networks

  Noda, K., Arie, H., Suga, Y. & Ogata, T., 2014 6月, In: Robotics and Autonomous Systems. 62, 6, p. 721-736 16 p.

  研究成果: Article › 査読

  • Robot 100%
  • Deep neural networks 79%
  • Neural Networks 76%
  • Learning 74%
  • Robots 52%
  112 被引用数 (Scopus)

• The interaction between a robot and multiple people based on spatially mapping of friendliness and motion parameters

  Tasaki, T., Ogata, T. & Okuno, H. G., 2014, In: Advanced Robotics. 28, 1, p. 39-51 13 p.

  研究成果: Article › 査読

  • Robots 100%
  • Sensors 45%
  • Factor analysis 25%
  4 被引用数 (Scopus)
• 2013

  Robust multipitch analyzer against initialization based on latent harmonic allocation using overtone corpus

  Sakaue, D., Itoyama, K., Ogata, T. & Okuno, H. G., 2013 4月, In: Journal of information processing. 21, 2, p. 246-255 10 p.

  研究成果: Article › 査読

  • Musical instruments 100%
  • Frequency estimation 87%
• 2012

  A multimodal tempo and beat-tracking system based on audiovisual information from live guitar performances

  Itohara, T., Otsuka, T., Mizumoto, T., Lim, A., Ogata, T. & Okuno, H. G., 2012, In: Eurasip Journal on Audio, Speech, and Music Processing. 2012, 1, 6.

  研究成果: Article › 査読

  • Audiovisual 100%
  • Pattern matching 98%
  • synchronism 75%
  • Hough transforms 50%
  • Optical flows 48%
  3 被引用数 (Scopus)

• A musical robot that synchronizes with a coplayer using non-verbal cues

  Lim, A., Mizumoto, T., Ogata, T. & Okuno, H. G., 2012, In: Advanced Robotics. 26, 3-4, p. 363-381 19 p.

  研究成果: Article › 査読

  • Robots 100%
  • Visual communication 54%
  • Audiovisual 44%
  • Agglomeration 33%
  • Synchronization 31%
  4 被引用数 (Scopus)

• Automated violin fingering transcription through analysis of an audio recording

  Maezawa, A., Itoyama, K., Komatani, K., Ogata, T. & Okuno, H. G., 2012 9月, In: Computer Music Journal. 36, 3, p. 57-72 16 p.

  研究成果: Article › 査読

  Open Access

  • Fingering 100%
  • Audio recordings 87%
  • Audio Recordings 85%
  • Fingerboard 82%
  • Violin 77%
  7 被引用数 (Scopus)

• Automatic allocation of training data for speech understanding based on multiple model combinations

  Komatani, K., Nakano, M., Katsumaru, M., Funakoshi, K., Ogata, T. & Okuno, H. G., 2012 9月, In: IEICE Transactions on Information and Systems. E95-D, 9, p. 2298-2307 10 p.

  研究成果: Article › 査読

  • Speech recognition 100%
  • Statistical methods 44%