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https://doi.org/10.21203/rs.3....
Article . 2021 . Peer-reviewed
License: CC BY
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The International Journal of Advanced Manufacturing Technology
Article . 2021 . Peer-reviewed
License: Springer TDM
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https://dx.doi.org/10.60692/3w...
Other literature type . 2021
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https://dx.doi.org/10.60692/cm...
Other literature type . 2021
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New model-based manipulation technique for reshaping deformable linear objects

تقنية معالجة جديدة قائمة على النموذج لإعادة تشكيل الأجسام الخطية القابلة للتشوه
Authors: Khalifa A.; Palli G.;

New model-based manipulation technique for reshaping deformable linear objects

Abstract

Abstract In this article, we consider the problem of reshaping a deformable linear object (DLO) like wires, cables, ropes, and surgical sutures. The solution to this problem would be useful for many fields, especially industrial manufacturing, where the DLO manipulation is still frequently carried out by human workers. In this work, a new model-based manipulation technique for reshaping a DLO is addressed employing a sequence of grasping and releasing primitives performed by a single-armed robot equipped with a gripper. A decision process selects the optimal grasping point exploiting an error minimization approach and chooses the related releasing point. This decision process performs a spline interpolation between the error values obtained from candidate grasping points and chooses the optimal point that owns a minimum error. The multivariate dynamic spline model of the DLO is exploited for selecting the optimal grasping point and predicting the DLO behavior during the manipulation process. Because of its advantages over other integration methods, the symplectic integrator is utilized for iteratively solving the DLO dynamic model. Simulation results of reshaping a DLO lying on a table are presented to evaluate the proposed technique. These results illustrate the intermediate deformation steps which lead the DLO from its starting state to the desired one. They demonstrate that our proposed technique can efficiently manipulate the DLO into various shapes in few steps.

Keywords

Artificial intelligence, Robotic Grasping and Learning from Demonstration, Kinematic and Dynamic Analysis of Robot Manipulators, Biomedical Engineering, Geometry, Soft Robotics, FOS: Medical engineering, Computer science, Process (computing), Kinematic Modeling, Operating system, Engineering, Point (geometry), Control and Systems Engineering, Dynamic Modeling, Physical Sciences, FOS: Mathematics, Object (grammar), Deformable linear object; Deformable object manipulation; Modeling and simulation; Robotic manipulation; Symplectic integrator, Design and Control of Soft Robotic Systems, Mathematics

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    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
hybrid