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Hiroshi Ito
Hiroshi Ito
Hitachi, Ltd. / Waseda University
Bestätigte E-Mail-Adresse bei hitachi.com
Titel
Zitiert von
Zitiert von
Jahr
Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control
H Ito, K Yamamoto, H Mori, T Ogata
Science Robotics 7 (65), eaax8177, 2022
492022
Contact-rich manipulation of a flexible object based on deep predictive learning using vision and tactility
H Ichiwara, H Ito, K Yamamoto, H Mori, T Ogata
2022 International Conference on Robotics and Automation (ICRA), 5375-5381, 2022
192022
Spatial attention point network for deep-learning-based robust autonomous robot motion generation
H Ichiwara, H Ito, K Yamamoto, H Mori, T Ogata
arXiv preprint arXiv:2103.01598, 2021
172021
Two-mode mapless visual navigation of indoor autonomous mobile robot using deep convolutional neural network
H Kanayama, T Ueda, H Ito, K Yamamoto
2020 IEEE/SICE International Symposium on System Integration (SII), 536-541, 2020
132020
Visual spatial attention and proprioceptive data-driven reinforcement learning for robust peg-in-hole task under variable conditions
AY Yasutomi, H Ichiwara, H Ito, H Mori, T Ogata
IEEE Robotics and Automation Letters 8 (3), 1834-1841, 2023
92023
Deep active visual attention for real-time robot motion generation: Emergence of tool-body assimilation and adaptive tool-use
H Hiruma, H Ito, H Mori, T Ogata
IEEE Robotics and Automation Letters 7 (3), 8550-8557, 2022
72022
Integrated learning of robot motion and sentences: Real-time prediction of grasping motion and attention based on language instructions
H Ito, H Ichiwara, K Yamamoto, H Mori, T Ogata
2022 International Conference on Robotics and Automation (ICRA), 5404-5410, 2022
72022
Effects of sedation on subjective perception of pain intensity and autonomic nervous responses to pain: A preliminary study
H Kang, A Nakae, H Ito, P Vitayaburananont, T Minamoto, T Ikeda, ...
Plos one 12 (9), e0183635, 2017
72017
Sensory-motor learning for simultaneous control of motion and force: Generating rubbing motion against uneven object
H Ito, T Kurata, T Ogata
2022 IEEE/SICE International Symposium on System Integration (SII), 408-415, 2022
52022
Evaluation of generalization performance of visuo-motor learning by analyzing internal state structured from robot motion
H Ito, K Yamamoto, H Mori, T Ogata
New Generation Computing 38, 7-22, 2020
52020
Visualization of focal cues for visuomotor coordination by gradient-based methods: A recurrent neural network shifts the attention depending on task requirements
H Ito, K Yamamoto, H Mori, S Goto, T Ogata
2020 IEEE/SICE International Symposium on System Integration (SII), 188-194, 2020
42020
Rapid prototyping for series of tasks in atypical environment: robotic system with reliable program-based and flexible learning-based approaches
H Ito, S Nakamura
ROBOMECH Journal 9 (1), 7, 2022
32022
深層学習を用いた要素動作の統合手法の開発
伊藤洋, 山本健次郎, 尾形哲也
ロボティクス・メカトロニクス講演会講演概要集 2018, 1A1-D09, 2018
32018
Field survey of visual comfort and energy efficiency in various office buildings utilizing daylight
H Ito, W Yuming, S Watanabe, S Tanabe
Proceedings of Indoor Air 2008 Conference, Copenhagen, Denmark 1722, 2008
32008
Multi-operation unit integration device, control method therefor, and autonomous learning type robot device
H Ito, K Yamamoto, Y Hieida
US Patent 11,440,185, 2022
22022
MTRNN を用いた End to End Learning による移動行動学習システムの開発
日永田佑介, 伊藤洋, 山本健二郎, 尾形哲也
ロボティクス・メカトロニクス講演会講演概要集 2017, 2A2-D11, 2017
22017
Moving Range Setting System and Moving Range Setting Method
H Kanayama, K Yamamoto, T Ueda, H Ito
US Patent App. 17/422,989, 2022
12022
Information processing device and information processing method
H Ito, K Yamamoto
US Patent App. 17/772,281, 2022
2022
Guided Visual Attention Model Based on Interactions Between Top-down and Bottom-up Prediction for Robot Pose Prediction
H Hiruma, H Mori, H Ito, T Ogata
IECON 2022–48th Annual Conference of the IEEE Industrial Electronics Society …, 2022
2022
触覚センサと深層学習を用いた布バッグのジッパー開け動作―日立-早大の共同研究開発事例―
一藁秀行, 伊藤洋, 山本健次郎, 森裕紀, 尾形哲也
ロボティクス・メカトロニクス講演会講演概要集 2021, 1P3-D04, 2021
2021
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