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Deformable Linear Objects (DLOs) such as ropes, cables, and surgical sutureshave a wide variety of uses in automotive engineering, surgery, andelectromechanical industries. Therefore, modeling of DLOs as well as acomputationally efficient way to predict the DLO behavior are of greatimportance, in particular to enable robotic manipulation of DLOs. The mainmotivation of this work is to enable efficient prediction of the DLO behaviorduring robotic manipulation. In this paper, the DLO is modeled by amultivariate dynamic spline, while a symplectic integration method is used tosolve the model iteratively by interpolating the DLO shape during themanipulation process. Comparisons between the symplectic, Runge-Kutta and Zhaiintegrators are reported. The presented results show the capabilities of thesymplectic integrator to overcome other integration methods in predicting theDLO behavior. Moreover, the results obtained with different sets of modelparameters integrated by means of the symplectic method are reported to showhow they influence the DLO behavior estimation.

Symplectic Integration for Multivariate Dynamic Spline-Based Model of Deformable Linear Objects