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dc.contributor.author
Kennel-Maushart, Florian
dc.contributor.author
Poranne, Roi
dc.contributor.author
Coros, Stelian
dc.date.accessioned
2021-12-23T13:33:51Z
dc.date.available
2021-12-23T13:23:30Z
dc.date.available
2021-12-23T13:33:51Z
dc.date.issued
2021
dc.identifier.isbn
978-1-7281-9077-8
en_US
dc.identifier.isbn
978-1-7281-9078-5
en_US
dc.identifier.other
10.1109/icra48506.2021.9561105
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/522184
dc.description.abstract
Teleoperation provides a way for human operators to guide robots in situations where full autonomy is challenging or where direct human intervention is required. It can also be an important tool to teach robots in order to achieve autonomous behaviour later on. The increased availability of collaborative robot arms and Virtual Reality (VR) devices, provides ample opportunity for development of novel teleoperation methods. Since robot arms are often kinematically different from human arms, mapping human motions to a robot in real-time is not trivial. Additionally, a human operator might steer the robot arm toward singularities or its workspace limits, which can lead to undesirable behaviour. This is further accentuated for the orchestration of multiple robots. In this paper, we present a VR interface targeted to multi-arm payload manipulation, which can closely match real-time input motion. Allowing the user to manipulate the payload rather than mapping their motions to individual arms we are able to simultaneously guide multiple collaborative arms. By releasing a single rotational degree of freedom, and by using a local optimization method, we can improve each arm’s manipulability index, which in turn lets us avoid kinematic singularities and workspace limitations. We apply our approach to predefined trajectories as well as real-time teleoperation on different robot arms and compare performance in terms of end-effector position error and relevant joint motion metrics.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
Robotics
en_US
dc.subject
Teleoperation
en_US
dc.subject
Multi-Robot System
en_US
dc.subject
Optimisation
en_US
dc.title
Manipulability optimization for multi-arm teleoperation
en_US
dc.type
Conference Paper
dc.date.published
2021-10-18
ethz.book.title
2021 IEEE International Conference on Robotics and Automation (ICRA)
en_US
ethz.pages.start
3956
en_US
ethz.pages.end
3962
en_US
ethz.event
2021 IEEE International Conference on Robotics and Automation (ICRA 2021)
en_US
ethz.event.location
Xi'an, China
en_US
ethz.event.date
30 May - 5 June, 2021
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02658 - Inst. Intelligente interaktive Systeme / Inst. Intelligent Interactive Systems::09620 - Coros, Stelian / Coros, Stelian
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02658 - Inst. Intelligente interaktive Systeme / Inst. Intelligent Interactive Systems::09620 - Coros, Stelian / Coros, Stelian
en_US
ethz.date.deposited
2021-12-23T13:23:35Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-12-23T13:33:57Z
ethz.rosetta.lastUpdated
2022-03-29T17:04:00Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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