Deformable Linear Objects (DLOs) such as ropes, cables, and surgical sutures have a wide variety of uses in automotive engineering, surgery, and electromechanical industries. Therefore, modeling of DLOs as well as a computationally efficient way to predict the DLO behavior are of great importance, in particular to enable robotic manipulation of DLOs. The main motivation of this work is to enable efficient prediction of the DLO behavior during robotic manipulation. In this paper, the DLO is modeled by a multivariate dynamic spline, while a symplectic integration method is used to solve the model iteratively by interpolating the DLO shape during the manipulation process. Comparisons between the symplectic, Runge-Kutta and Zhai integrators are reported. The presented results show the capabilities of the symplectic integrator to overcome other integration methods in predicting the DLO behavior. Moreover, the results obtained with different sets of model parameters integrated by means of the symplectic method are reported to show how they influence the DLO behavior estimation.

翻译：线性变形物体(DLOs),如绳索、电缆和外科缝合线(DLOs),在汽车工程、手术和电动机械工业中具有多种用途。因此,DLO的建模以及预测DLO行为的计算高效方式非常重要,特别是为了便于对DLO进行机器人操作。这项工作的主要动机是能够有效预测机器人操作过程中的DLO行为。在本文中,DLO是由多变量动态样板模拟的,同时采用静态集成法,在操作过程中通过对DLO形状进行相互迭接解决模型。报告了对Sympectic、Runge-Kutta和Zhai Intractors的比较。介绍的结果显示,在预测DLO行为时,静态集成器有能力克服其他集成方法。此外,还报告了通过通过模拟方法整合的不同模型参数获得的结果,以显示它们如何影响DLO行为估计。