TU Darmstadt / ULB / TUbiblio

Assisted teleoperation in changing environments with a mixture of virtual guides

Ewerton, Marco ; Arenz, Oleg ; Peters, Jan (2022)
Assisted teleoperation in changing environments with a mixture of virtual guides.
In: Advanced Robotics, 34 (18)
doi: 10.26083/tuprints-00023003
Artikel, Zweitveröffentlichung, Postprint

Kurzbeschreibung (Abstract)

Haptic guidance is a powerful technique to combine the strengths of humans and autonomous systems for teleoperation. The autonomous system can provide haptic cues to enable the operator to perform precise movements; the operator can interfere with the plan of the autonomous system leveraging his/her superior cognitive capabilities. However, providing haptic cues such that the individual strengths are not impaired is challenging because low forces provide little guidance, whereas strong forces can hinder the operator in realizing his/her plan. Based on variational inference, we learn a Gaussian mixture model (GMM) over trajectories to accomplish a given task. The learned GMM is used to construct a potential field which determines the haptic cues. The potential field smoothly changes during teleoperation based on our updated belief over the plans and their respective phases. Furthermore, new plans are learned online when the operator does not follow any of the proposed plans or after changes in the environment. User studies confirm that our framework helps users perform teleoperation tasks more accurately than without haptic cues and, in some cases, faster. Moreover, we demonstrate the use of our framework to help a subject teleoperate a 7 DoF manipulator in a pick-and-place task.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Ewerton, Marco ; Arenz, Oleg ; Peters, Jan
Art des Eintrags: Zweitveröffentlichung
Titel: Assisted teleoperation in changing environments with a mixture of virtual guides
Sprache: Englisch
Publikationsjahr: 2022
Ort: Darmstadt
Verlag: Taylor & Francis
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Advanced Robotics
Jahrgang/Volume einer Zeitschrift: 34
(Heft-)Nummer: 18
Kollation: 19 Seiten
DOI: 10.26083/tuprints-00023003
URL / URN: https://tuprints.ulb.tu-darmstadt.de/23003
Zugehörige Links:
Herkunft: Zweitveröffentlichungsservice
Kurzbeschreibung (Abstract):

Haptic guidance is a powerful technique to combine the strengths of humans and autonomous systems for teleoperation. The autonomous system can provide haptic cues to enable the operator to perform precise movements; the operator can interfere with the plan of the autonomous system leveraging his/her superior cognitive capabilities. However, providing haptic cues such that the individual strengths are not impaired is challenging because low forces provide little guidance, whereas strong forces can hinder the operator in realizing his/her plan. Based on variational inference, we learn a Gaussian mixture model (GMM) over trajectories to accomplish a given task. The learned GMM is used to construct a potential field which determines the haptic cues. The potential field smoothly changes during teleoperation based on our updated belief over the plans and their respective phases. Furthermore, new plans are learned online when the operator does not follow any of the proposed plans or after changes in the environment. User studies confirm that our framework helps users perform teleoperation tasks more accurately than without haptic cues and, in some cases, faster. Moreover, we demonstrate the use of our framework to help a subject teleoperate a 7 DoF manipulator in a pick-and-place task.

Freie Schlagworte: teleoperation; policy search; variational inference; movement primitives; Gaussian mixture models
Status: Postprint
URN: urn:nbn:de:tuda-tuprints-230039
Zusätzliche Informationen:

Supplement (video): https://doi.org/10.6084/m9.figshare.12852846.v1

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Intelligente Autonome Systeme
Hinterlegungsdatum: 14 Dez 2022 13:48
Letzte Änderung: 19 Dez 2022 09:55
PPN:
Zugehörige Links:
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen