Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation
Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China..
Yale Univ, Dept Mech Engn & Mat Sci, New Haven, CT USA..
Hong Kong Univ Sci & Technol, Dept Mech & Aerosp Engn, Hong Kong, Peoples R China..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2965-2953
Show others and affiliations
2019 (English)In: 2019 International Conference on Robotics and Automation (ICRA) / [ed] Howard, A Althoefer, K Arai, F Arrichiello, F Caputo, B Castellanos, J Hauser, K Isler, V Kim, J Liu, H Oh, P Santos, V Scaramuzza, D Ude, A Voyles, R Yamane, K Okamura, A, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 2153-2160Conference paper, Published paper (Refereed)
Abstract [en]

Moving a human body or a large and bulky object may require the strength of whole arm manipulation (WAM). This type of manipulation places the load on the robot's arms and relies on global properties of the interaction to succeed-rather than local contacts such as grasping or non-prehensile pushing. In this paper, we learn to generate motions that enable WAM for holding and transporting of humans in certain rescue or patient care scenarios. We model the task as a reinforcement learning problem in order to provide a robot behavior that can directly respond to external perturbation and human motion. For this, we represent global properties of the robot-human interaction with topology-based coordinates that are computed from arm and torso positions. These coordinates also allow transferring the learned policy to other body shapes and sizes. For training and evaluation, we simulate a dynamic sea rescue scenario and show in quantitative experiments that the policy can solve unseen scenarios with differently-shaped humans, floating humans, or with perception noise. Our qualitative experiments show the subsequent transporting after holding is achieved and we demonstrate that the policy can be directly transferred to a real world setting.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 2153-2160
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-265483DOI: 10.1109/ICRA.2019.8794160ISI: 000494942301099Scopus ID: 2-s2.0-85068443674ISBN: 978-1-5386-6026-3 (print)ISBN: 978-1-5386-6027-0 (electronic)OAI: oai:DiVA.org:kth-265483DiVA, id: diva2:1379604
Conference
2019 International Conference on Robotics and Automation, ICRA 2019; Palais des Congres de Montreal, Montreal; Canada; 20-24 May 2019
Note

QC 20191217

Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2020-01-31Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopusConference websiteConference proceedings

Authority records BETA

Kragic, DanicaStork, Johannes A.

Search in DiVA

By author/editor
Kragic, DanicaStork, Johannes A.
By organisation
Robotics, Perception and Learning, RPLCentre for Autonomous Systems, CAS
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 16 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf