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Calibration of an Elastic Humanoid Upper Body and Efficient Compensation for Motion Planning

Tenhumberg, Johannes und Bäuml, Berthold (2021) Calibration of an Elastic Humanoid Upper Body and Efficient Compensation for Motion Planning. In: 20th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2020. IEEE. IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids), 2021-07-19 - 2021-07-21, Munich, Germany. doi: 10.1109/HUMANOIDS47582.2021.9555793. ISBN 978-172819372-4. ISSN 2164-0572.

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Offizielle URL: https://ieeexplore.ieee.org/abstract/document/9555793

Kurzfassung

High absolute accuracy is an essential prerequisite for a humanoid robot to autonomously and robustly perform manipulation tasks while avoiding obstacles. We present for the first time a kinematic model for a humanoid upper body incorporating joint and transversal elasticities. These elasticities lead to significant deformations due to the robot's own weight, and the resulting model is implicitly defined via a torque equilibrium. We successfully calibrate this model for DLR's humanoid Agile Justin, including all Denavit-Hartenberg parameters and elasticities. The calibration is formulated as a combined least-squares problem with priors and based on measurements of the end effector positions of both arms via an external tracking system. The absolute position error is massively reduced from 21mm to 3.1mm on average in the whole workspace. Using this complex and implicit kinematic model in motion planning is challenging. We show that for optimization-based path planning, integrating the iterative solution of the implicit model into the optimization loop leads to an elegant and highly efficient solution. For mildly elastic robots like Agile Justin, there is no performance impact, and even for a simulated highly flexible robot with 20 times higher elasticities, the runtime increases by only 30%.

elib-URL des Eintrags:https://elib.dlr.de/146302/
Dokumentart:Konferenzbeitrag (Poster)
Titel:Calibration of an Elastic Humanoid Upper Body and Efficient Compensation for Motion Planning
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Tenhumberg, JohannesJohannes.Tenhumberg (at) dlr.dehttps://orcid.org/0000-0002-5090-1259NICHT SPEZIFIZIERT
Bäuml, BertholdBerthold.Baeuml (at) dlr.dehttps://orcid.org/0000-0002-4545-4765NICHT SPEZIFIZIERT
Datum:20 Juli 2021
Erschienen in:20th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2020
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.1109/HUMANOIDS47582.2021.9555793
Verlag:IEEE
ISSN:2164-0572
ISBN:978-172819372-4
Status:veröffentlicht
Stichwörter:robotics, calibration, motion planning
Veranstaltungstitel:IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)
Veranstaltungsort:Munich, Germany
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:19 Juli 2021
Veranstaltungsende:21 Juli 2021
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Robotik
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R RO - Robotik
DLR - Teilgebiet (Projekt, Vorhaben):R - Autonome, lernende Roboter [RO]
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Robotik und Mechatronik (ab 2013)
Hinterlegt von: Tenhumberg, Johannes
Hinterlegt am:08 Dez 2021 14:25
Letzte Änderung:24 Apr 2024 20:45

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