International Journal of Advanced Robotic Systems (Apr 2023)

An improved numerical model for locomotive tensegrity systems based on vector form intrinsic finite element

  • Xian Xu,
  • Meijia Wang,
  • Yanfeng Zheng,
  • Chunlin Zhou,
  • Yaozhi Luo

DOI
https://doi.org/10.1177/17298806231162442
Journal volume & issue
Vol. 20

Abstract

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Locomotive robot based on tensegrity has recently drawn much attention due to its lightweight and flexibility. This article presents an improved numerical model for locomotive tensegrities. The previously used bar element for struts is replaced by beam element, and rigid joint element is used to consider more details of the tendon–strut connections. The vector form intrinsic finite element (VFIFE) method is adopted to formulate the numerical model and carry out the simulation. The improvement of the proposed model on the prediction of feasible rolling gaits is quantitatively verified by experiments on a six-strut locomotive tensegrity. Mann–Whitney U test is adopted, and the p value between the experimental success rates of the gait primitives generated by the improved model and the rates of the gait primitives generated by the previous model is 1.46 × 10 − 12 . It is shown that the improved model is more consistent with the experiment by considering the details of the tendon–strut connection.