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A Practical Force Correction Method for Over-Constrained Cable-Driven Parallel Robots

: Fabritius, Marc; Martin, C.; Gomez, G.R.; Kraus, W.; Pott, A.

Volltext urn:nbn:de:0011-n-6381557 (462 KByte PDF)
MD5 Fingerprint: 4b4c3c87f8c18fa91c3713c2166dea1c
The original publication is available at
Erstellt am: 28.7.2021

Gouttefarde, M.:
Cable-Driven Parallel Robots : Proceedings of the 5th International Conference on Cable-Driven Parallel Robots (CableCon 2021), held as virtual event, July 7-9, 2021
Cham: Springer Nature, 2021 (Mechanisms and Machine Science 104)
ISBN: 978-3-030-75788-5 (Print)
ISBN: 978-3-030-75789-2 (Online)
International Conference on Cable-Driven Parallel Robots (CableCon) <5, 2021, Online>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
Simulation; Arbeitsplatz; Paralleler Seilroboter; Seilroboter; Stellenbeschreibung

Cable-driven parallel robots can have a much larger workspace than other parallel robots with rigid links or conventional serial robots. This property comes at the cost of more complex workspace calculations and control schemes that are necessary to account for the elasticity and unilateral force transmission of their parallel cable links. In practice, most cable-driven parallel robots cannot achieve the full workspace that is predicted by theoretical models. This is due to calibration errors and simplified modelling assumptions in the control schemes. While most previous works on this subject have focused on creating more accurate and complex models, the goal of this work is to increase the workspace volume that cable-driven parallel robots can realize in practice by using a simple model coupled with a new force correction method that is robust to modelling errors and uncertainties. The new method applies force corrections within the nullspace of the structure matrix in order to keep the cable forces within their limits. Experiments show that the new method can significantly increase the workspace when used in addition to basic kinematic codes. In simulations this combination achieves the same workspace as complex controllers that require the precise knowledge of many additional model parameters.