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Kuniyuki Takahashi
Kuniyuki Takahashi
Preferred Networks, Inc. Researcher
Verified email at preferred.jp - Homepage
Title
Cited by
Cited by
Year
Interactively picking real-world objects with unconstrained spoken language instructions
J Hatori*, Y Kikuchi*, S Kobayashi*, K Takahashi*, Y Tsuboi*, Y Unno*, ...
2018 IEEE International Conference on Robotics and Automation (ICRA), 3774-3781, 2018
992018
Deep Visuo-Tactile Learning: Estimation of Tactile Properties from Images
K Takahashi, J Tan
2019 IEEE/RSJ International Conference Robotics and Automation (ICRA2019), 2019
35*2019
Tool-body assimilation model considering grasping motion through deep learning
K Takahashi, K Kim, T Ogata, S Sugano
Robotics and Autonomous Systems 91, 115-127, 2017
332017
Dynamic Motion Learning for Multi-DOF Flexible-Joint Robots Using Active-Passive Motor Babbling through Deep Learning
K Takahashi, T Ogata, J Nakanishi, G Cheng, S Sugano
Advanced Robotics 31 (18), 1002-1015, 2017
192017
Neural network based model for visual-motor integration learning of robot's drawing behavior: Association of a drawing motion from a drawn image
K Sasaki, H Tjandra, K Noda, K Takahashi, T Ogata
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
192015
Tool-body assimilation model based on body babbling and neurodynamical system
K Takahashi, T Ogata, H Tjandra, Y Yamaguchi, S Sugano
Mathematical Problems in Engineering 2015, 2015
192015
Map-based multi-policy reinforcement learning: enhancing adaptability of robots by deep reinforcement learning
A Kume, E Matsumoto, K Takahashi, W Ko, J Tan
arXiv preprint arXiv:1710.06117, 2017
132017
Effective motion learning for a flexible-joint robot using motor babbling
K Takahashi, T Ogata, H Yamada, H Tjandra, S Sugano
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
102015
Deep Gated Multi-modal Learning: In-hand Object Pose Changes Estimation using Tactile and Image Data
T Anzai*, K Takahashi*
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
7*2020
Tool-body assimilation model based on body babbling and a neuro-dynamical system for motion generation
K Takahashi, T Ogata, H Tjandra, S Murata, H Arie, S Sugano
International Conference on Artificial Neural Networks, 363-370, 2014
42014
Tool-body assimilation model using a neuro-dynamical system for acquiring representation of tool function and motion
K Takahshi, T Ogata, H Tjandra, Y Yamaguchi, Y Suga, S Sugano
2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2014
42014
Uncertainty-Aware Self-Supervised Target-Mass Grasping of Granular Foods
K Takahashi, W Ko, A Ummadisingu, S Maeda
2021 IEEE International Conference on International Conference on Robotics …, 2021
32021
Handling and grasp control with additional grasping point for dexterous manipulation of cylindrical tool
T Sugaiwa, K Takahashi, H Kano, H Iwata, S Sugano
2011 IEEE International Conference on Robotics and Biomimetics, 733-738, 2011
32011
Conditional generative adversarial networks によるロボットアームの障害物回避軌道計画
鳥島亮太, 森裕紀, 高橋城志, 岡野原大輔, 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 2019, 1P2-A14, 2019
22019
Effective input order of dynamics learning tree
CH Kim, S Hama, R Hirai, K Takahashi, H Yamada, T Ogata, S Sugano
Advanced Robotics 32 (3), 122-136, 2018
22018
Efficient Motor Babbling Using Variance Predictions from a Recurrent Neural Network
K Takahashi, K Suzuki, T Ogata, H Tjandra, S Sugano
22nd International Conference on Neural Information Processing (ICONIP2015 …, 2015
22015
Dynamic Motion Learning for a Flexible-Joint Robot using Active-Passive Motor Babbling
K Takahashi, T Ogata, S Sugano, G Cheng
The 33st Annual Conference of the Robotics Society of Japan, 2G1-07, 2015
22015
Target-mass Grasping of Entangled Food using Pre-grasping & Post-grasping
K Takahashi, N Fukaya, A Ummadisingu
IEEE Robotics and Automation Letters (RA-L) 7 (2), 1222-1229, 2022
12022
cGANs の潜在空間を用いた複数の障害物条件におけるロボットの衝突回避計画
安藤智貴, 森裕紀, 鳥島亮太, 高橋城志, 山口正一朗, 岡野原大輔, ...
ロボティクス・メカトロニクス講演会講演概要集 2020, 1P1-G04, 2020
12020
触覚センサと深層学習を用いたマニピュレーション
高橋城志
日本ロボット学会誌 38 (6), 521-524, 2020
12020
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