Natural Language Processing in Robotics
Author:
Affiliation:
1. The Institute of Statistical Mathematics
Publisher
The Robotics Society of Japan
Link
https://www.jstage.jst.go.jp/article/jrsj/39/5/39_39_399/_pdf
Reference27 articles.
1. 1) M. Nagano, T. Nakamura, T. Nagai, D. Mochihashi, I. Kobayashi and M. Kaneko: “Sequence Pattern Extraction by Segmenting Time Series Data Using GP-HSMM with Hierarchical Dirichlet Process,” IROS 2018, pp.4067–4074, 2018.
2. 2) M. Nagano, T. Nakamura, T. Nagai, D. Mochihashi, I. Kobayashi and W. Takano: “High-dimensional Motion Segmentation by Variational Autoencoder and Gaussian Processes,” IROS 2019, pp.105–111, 2019.
3. 3) D. Mochihashi: “Gaussian Process Generative Models for Language and Robotics,” CoRL 2019 Tutorial, 2019.
4. 4) T. Taniguchi, D. Mochihashi, T. Nagai, S. Uchida, N. Inoue, I. Kobayashi, T. Nakamura, Y. Hagiwara, N. Iwahashi and T. Inamura: “Survey on frontiers on language and robotics,” Advanced Robotics, vol.33, no.15–16, pp.700–730, 2019.
5. 5) J. Hatori, Y. Kikuchi, S. Kobayashi, K. Takahashi, Y. Tsuboi, Y. Unno, W. Ko and J Tan: “Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions,” ICRA 2018, pp.3774–3781, 2018.
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