Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning

Marco Ewerton, Guilherme Maeda, Dorothea Koert, Zlatko Kolev, Masaki Takahashi, Jan Peters

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

The majority of learning from demonstration approaches do not address suboptimal demonstrations or cases when drastic changes in the environment occur after the demonstrations were made. For example, in real teleoperation tasks, the demonstrations provided by the user are often suboptimal due to interface and hardware limitations. In tasks involving co-manipulation and manipulation planning, the environment often changes due to unexpected obstacles rendering previous demonstrations invalid. This paper presents a reinforcement learning algorithm that exploits the use of relevance functions to tackle such problems. This paper introduces the Pearson correlation as a measure of the relevance of policy parameters in regards to each of the components of the cost function to be optimized. The method is demonstrated in a static environment where the quality of the teleoperation is compromised by the visual interface (operating a robot in a three-dimensional task by using a simple 2D monitor). Afterward, we tested the method on a dynamic environment using a real 7-DoF robot arm where distributions are computed online via Gaussian Process regression.

本文言語English
ホスト出版物のタイトル2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ4294-4300
ページ数7
ISBN(電子版)9781728140049
DOI
出版ステータスPublished - 2019 11月
イベント2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
継続期間: 2019 11月 32019 11月 8

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
国/地域China
CityMacau
Period19/11/319/11/8

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

フィンガープリント

「Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning」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