Multi-Objective Optimization of Motion Control for 6-Bar 18-Cable Tensegrity Structure Based on Jaya Algorithm

Abstract Tensegrity structures, celebrated for their lightweight design, high efficiency, and shape adaptability, have broad application prospects in structural engineering, aerospace, robotics, and other interdisciplinary fields. Due to the geometric structure of the classic 6-bar 24-cable tensegrity robot (TR-0624), which leads to poor steering control and significant path deviation during path planning, this article introduces a 6-bar 18-cable tensegrity robot (TR-0618) based on a truncated tetrahedron to address this issue. First, the dynamic equation of TR-0618 is developed, and the Jaya algorithm is applied for single-objective optimization focusing on centroid offset, as well as dual-objective optimization considering centroid offset alongside energy or internal space. The Jaya algorithm in matlab is employed to determine an effective driving strategy for the basic gait of TR-0618. Next, a weight-based dual-objective optimization method is proposed to identify the driving strategy for the basic gait characteristics of TR-0618. By combining the basic gaits, a comparison is conducted on the 4 m straight path and across four geometric paths with TR-0624. Finally, the physical model of TR-0618 is designed and manufactured, followed by wireless control experiments to validate its basic gait and path-planning capabilities, the effectiveness of the TR-0618 motion control multi-objective optimization methods is verified.