Abstract

The dataset contains the data related to the numerical integration of Deformable linear objects (DLOs) such as ropes, cables, and surgical sutures comparing different numerical methods. The main motivation of this work is to enable efficient prediction of the DLO behavior during robotic manipulation. 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 in the dataset. 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. The data are presented in the publication: Khalifa A., Palli G., “Symplectic Integration for Multivariate Dynamic Spline-Based Model of Deformable Linear Objects”, Journal of Computational and Nonlinear Dynamics, 17 (1), art. no. 011001, 2022, DOI: 10.1115/1.4052571.