Extended Reproduction of Demonstration Motion Using Variational Autoencoder

Daisuke Takahashi, Seiichiro Katsura

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Learning from demonstration (LfD) is an effective method for robot motion learning because hand-coded cost function is not necessary. However, the number of times demonstrations can be performed is limited and performing a demonstration in every environmental condition is difficult. Therefore, an algorithm for generating a motion data not obtained by demonstrations is required. In order to deal with this problem, this research generates motion latent space by abstracting the demonstration data. Motion latent space is a space expressing the demonstration motion in lower dimensions. Also the demonstration data can be extended by decoding the points in the latent space. These things are realized by applying variational autoencoder (VAE) used in the field of image generation to time-series data. Demonstrations of the reaching task are conducted, and the paper shows that the manipulator can reach the object even when the object is located at a different position from demonstrations.

本文言語English
ホスト出版物のタイトルProceedings - 2018 IEEE 27th International Symposium on Industrial Electronics, ISIE 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1057-1062
ページ数6
ISBN(印刷版)9781538637050
DOI
出版ステータスPublished - 2018 8月 10
イベント27th IEEE International Symposium on Industrial Electronics, ISIE 2018 - Cairns, Australia
継続期間: 2018 6月 132018 6月 15

出版物シリーズ

名前IEEE International Symposium on Industrial Electronics
2018-June

Other

Other27th IEEE International Symposium on Industrial Electronics, ISIE 2018
国/地域Australia
CityCairns
Period18/6/1318/6/15

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 制御およびシステム工学

フィンガープリント

「Extended Reproduction of Demonstration Motion Using Variational Autoencoder」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル