SKID RAW: Skill Discovery from Raw Trajectories

Daniel Tanneberg, Kai Ploeger, Elmar Rueckert, Jan Peters

Publikation: Beitrag in FachzeitschriftArtikelForschungBegutachtung

1 Zitat (Scopus)
OriginalspracheEnglisch
Aufsatznummer9387162
Seiten (von - bis)4696-4703
Seitenumfang8
FachzeitschriftIEEE Robotics and Automation Letters
Jahrgang6
Ausgabenummer3
DOIs
PublikationsstatusVeröffentlicht - Juli 2021

Bibliographische Notiz

Funding Information:
Manuscript received December 2, 2020; accepted March 8, 2021. Date of publication March 25, 2021; date of current version April 13, 2021. This letter was recommended for publication by Associate Editor M. Burke and Editor D. Kulic upon evaluation of the reviewers’ comments. This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 713010 (GOAL-Robots) and 640554 (SKILLS4ROBOTS), in part by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -No. 430054590 (TRAIN), and in part by NVIDIA. (Corresponding author: Daniel Tanneberg.) Daniel Tanneberg and Kai Ploeger are with the Intelligent Autonomous Systems, Technische Universität Darmstadt, 64289 Darmstadt, Germany (e-mail: daniel@robot-learning.de; kai.ploeger@tu-darmstadt.de).

Publisher Copyright:
© 2016 IEEE.

Schlagwörter

  • robot motion control
  • learning
  • movement primitives

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