How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance

Tendon actuation is one of the most prominent actuation principles for continuum robots. To date, a wide variety of modelling approaches has been derived to describe the deformations of tendon-driven continuum robots. Motivated by the need for a comprehensive overview of existing methodologies, this...

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Veröffentlicht in:Frontiers in robotics and AI Jg. 7; S. 630245
Hauptverfasser: Rao, Priyanka, Peyron, Quentin, Lilge, Sven, Burgner-Kahrs, Jessica
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland Frontiers Media S.A 02.02.2021
Schlagworte:
modelling
Robotics and AI
soft arm
soft manipulator
soft robot
tendon actuation
soft manipulator
modelling
soft arm
soft robot
tendon actuation
ISSN:2296-9144, 2296-9144
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Zusammenfassung:Tendon actuation is one of the most prominent actuation principles for continuum robots. To date, a wide variety of modelling approaches has been derived to describe the deformations of tendon-driven continuum robots. Motivated by the need for a comprehensive overview of existing methodologies, this work summarizes and outlines state-of-the-art modelling approaches. In particular, the most relevant models are classified based on backbone representations and kinematic as well as static assumptions. Numerical case studies are conducted to compare the performance of representative modelling approaches from the current state-of-the-art, considering varying robot parameters and scenarios. The approaches show different performances in terms of accuracy and computation time. Guidelines for the selection of the most suitable approach for given designs of tendon-driven continuum robots and applications are deduced from these results.
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Reviewed by: Ashwin K. P., FeatherDyn Pvt Ltd., India
Edited by: Matteo Cianchetti, Sant’Anna School of Advanced Studies, Italy
Kristin M. De Payrebrune, University of Kaiserslautern, Germany
This article was submitted to Soft Robotics, a section of the journal Frontiers in Robotics and AI
ISSN:2296-9144
2296-9144
DOI:10.3389/frobt.2020.630245