English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse
  1. Item Summary / 
  2. View item

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Unsupervised Contact Learning for Humanoid Estimation and Control

Rotella, N., Schaal, S., & Righetti, L. (2018). Unsupervised Contact Learning for Humanoid Estimation and Control. In 2018 IEEE International Conference on Robotics and Automation (ICRA 2018) (pp. 411-417). Piscataway, NJ, USA: IEEE. doi:10.1109/ICRA.2018.8462864.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-0003-6311-A Version Permalink: https://hdl.handle.net/21.11116/0000-0004-7D69-B
Genre: Conference Paper

Files

show Files

Locators

show
hide
Locator:
Link (Any fulltext)
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Rotella, Nicholas1, Author
Schaal, Stefan2, Author           
Righetti, Ludovic3, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Autonomous Motion, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497646              
3Research Group Movement Generation and Control, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_2344693              

Content

show
hide
Free keywords: Abt. Schaal; Forschungsgruppe Righetti
 Abstract: -

Details

show
hide
Language(s): eng - English
 Dates: 2018-09-132018
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: rotella_unsupervised_2018
DOI: 10.1109/ICRA.2018.8462864
 Degree: -

Event

show
hide
Title: IEEE International Conference on Robotics and Automation (ICRA 2018)
Place of Event: Brisbane
Start-/End Date: 2018-05-21 - 2018-05-25

Legal Case

show

Project information

show

Source 1

show
hide
Title: 2018 IEEE International Conference on Robotics and Automation (ICRA 2018)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 411 - 417 Identifier: ISBN: 978-1-5386-3081-5
ISBN: 978-1-5386-3080-8
ISBN: 978-1-5386-3082-2
ISSN: 2577-087X