ロボティクスと深層学習. Robotics and Deep Learning. Keywords: robotics, deep learning, multimodal learning, end to end learning, sequence to sequence learning.

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1 ニューラルネットワーク研究のフロンティア ロボティクスと深層学習 Robotics and Deep Learning 尾形哲也 Tetsuya Ogata Waseda University. ogata@waseda.jp, Keywords: robotics, deep learning, multimodal learning, end to end learning, sequence to sequence learning. 1. はじめに Deep Learning DL,,,,.DL, 10.,,,,,.,,,.,,,,DL.,. DL,,, DL.,,,,,,DL..,,,, DL., DL.,2,3,, 4, 認識と状態評価,,.,, DL.,Ian Lenz,DL 4 [Lenz 14] 1. Y. Yang,DL CNN Convolutional Neural Network,YouTube, 48 6 [Yang 15]. 図 1 Baxter [Lenz 14]

2 211,DL. DL,Deep Q-Learning [Mnih 13].,, s a Q,.,. Q-Learning. Deep Q-Learning,DL. Atari2600 7, pixel,4,4 18, Q.,, DL Q.,. DL,.,DL.,,., End to End Learning,DL. S. Levine,PR2, 1 CNN,.,, [Levine 15]. 2., End to End Learning,,. 1,. 3. 運動の生成 Deep Q-Learning,,.,, 4,, 6. s, a,,., DL,,,.,,.,.,. DL, 図 2 PR2 [Levine 15] S. Levine, [Noda 14].,,. CNN, Time-delay Deep Autoencoder DA,. 3.,,, DA. Aldebaran Robotics NAO, , DA, 30.

3 図 3 DL 図 5 Ball lift Ball roll Ball ring L 図 4 NAO, HMM DA.,30 1,1 Time delay NN.,,. 5.,, 6.,,.,,, DL,.,.,,,,3 000 図 6. a, b 図 7 PR2, 6. DL,,.,. PR2,7 7 [ 16] cm.,,

4 213,,.,DL,,,.. 4. 言語と動作,.,,.,2 Y. Yang,DL,,., Recurrent Neural Network RNN,..RNN,, DL Back Propagation Through Time BPTT. DL., RNN,MTRNN Multi Timescale RNN [Yamashita 14] LSTM Long Short Term Memory [Hochreiter 97], RNN. RNN,,. Sequence to Sequence Learning [Sutskever 14], 2 RNN., End to End Learning.,RNN DL,.,Google Vinyals CNN, RNN, Image Caption Generator [Levine 15, Vinyals 15]., Sequence to Sequence Learning,., [Yamada 15]. 8. 図 8 Sequence to Sequence Learning RNN,,,., NAO.NAO, 2, Red, Green, Blue,., 3. 3.,.,.,,,,.,,,.,,,RNN. 図 9

5 図 10 3,5 RNN,,.,,. 1,2..,,. 10 3,5.,Red, Green, Blue,. 1,2, 3,5..,,, MTRNN LSTM,. 5. まとめ,DL,,,,,.1,DL,,.,,. DL RNN,,. DL,RNN. DL,. DL,Batch,,. DL Batch,. RNN,,.DL,.,,.DL,,,.4 RNN,, [Takahashi 15],. DL.,,,3 4,,,.,.,Pinto Baxter [Pinto 15].,.,,. [JST CREST 15].,,,.,

6 215 DeepMind AlphaGo, CNN, CNN [Silver 16]. DL,.,.,,,.. 4,DL RNN, 1,2, 3,5. RNN.,,..,, DL RNN,. 謝辞,JST..,,,,,,.. 参考文献 [Hochreiter 97] Hochreiter, S. and Schmidhuber, J.: Long shortterm memory, Neural Computation, Vol. 9 No. 8, pp [JST CREST 15] JST CREST, [Lenz 14] Lenz, I., Lee, H. and Saxena, A.: Deep learning for detecting robotic grasps, Int. J. Robotics Research IJRR 2014 [Levine 15] Levine, S., Finn, C., Darrell, T. and Abbeel, P.: Endto-End Training of Deep Visuomotor Policies, arxiv: [Mnih 13] Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D. and Riedmiller, M.: Playing atari with deep reinforcement learning, Deep Learning Workshop NIPS [Noda 14] Noda, K., Arie, H., Suga, Y. and Ogata, T.: Multimodal integration learning of robot behavior using deep neural networks, Robotics and Autonomous Systems, Vol. 62, No. 6, pp [Pinto 15] Pinto, L. and Gupta, A.: Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours, arxiv: [Silver 16] Silver, D., et al.: Mastering the game of Go with deep neural networks and tree search, Nature, Vol. 529, Issue 7587, pp [Sutskever 14] Sutskever, I., Vinyals, O. and Le, Q. V.: Sequence to sequence learning with neural networks, NIPS 2014, pp [ 16],,Gordon Cheng,, [Takahashi 15] Takahashi, K., Ogata, T., Yamada, H., Tjandra, H. and Sugano, S.: Effective motion learning for a flexible-joint robot using motor babbling, Proc IEEE/RAS Int. Conf. on Intelligent Robots and Systems IROS [Vinyals 15] Vinyals, O., Toshev, A., Bengio, S. and Erhan, D.: Show and Tell: A Neural Image Caption Generator, arxiv: [Yamada 15a] Yamada, T., Murata, S., Arie, H. and Ogata, T.: Attractor representations of language-behavior structure in a recurrent neural network for human-robot interaction, Proc IEEE/RAS Int. Conf. on Intelligent Robots and Systems IROS [Yamashita 08] Yamashita, Y. and Tani, J.: Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment, PLoS Computational Biology, Vol. 4, Issue. 11, e [Yang 15] Yang, Y., Li, Y., Fermüller, C. and Aloimonos, Y.: Robot learning manipulation action plans by Watching unconstrained videos from the world wide web, 28th AAAI Conf. on Artificial Intelligence 著者紹介 尾形哲也 DC2,1999,2001,2003, , JST,2015..,,,,,IEEE.