Large Torsion Thin Artificial Muscles Tensegrity Structure for Twist Manipulation

Abstract

Tensegrity structures have been actively studied in recent years because they are lightweight, compliant, and flexible, which are properties not typically found in conventional robots. This structure can be modularized to create soft robots that operate in unknown environments such as cave or space with more complex and effective behavior. The basic deformation elements in modularization are stretching, bending, and torsion. Among them, torsional motion is important for proper manipulation and rotational operation. However, active, and large torsion in soft tensegrity structures has not been developed. Therefore, this study describes torsional deformation and a novel arrangement method for thin artificial muscles. The proposed method leads to the optimal placement of artificial muscles for torsion, by which we generated a large torsion of ±50 deg. This is more than 2.5 times larger than that of a previous tensegrity without compromising the favorable properties of the structure. Furthermore, by modularizing the tensegrity structure, a tensegrity arm capable of removing a plastic bottle cap was developed. The applicability of torsional deformation and the usefulness of modularization of the structure are demonstrated.

Active-Bending Six-Bar Tensegrity Modular Robot Driven by Thin Artificial Muscles

“…In this study, performing a coupled analysis of the force characteristics of the artificial muscle with a conventional tensegrity structural analysis is necessary when considering the force balance of a tensegrity structure integrated with an artificial muscle. Therefore, the authors performed numerical static analyses based on the potential energy in [6] and [11]. In this study, the similar statistical analysis was used.…”

“…Therefore, our aim is to establish a versatile design method for tensegrity robots to develop a six-bar tensegrity robot that can perform contraction, torsion, and bending [6] [11]. Furthermore, employing a recurrent neural network (RNN), we aim to realize shape recognition of the surrounding environment by estimating the shape of the tensegrity robot [12].…”

“…Furthermore, employing a recurrent neural network (RNN), we aim to realize shape recognition of the surrounding environment by estimating the shape of the tensegrity robot [12]. We presented a module that produces large stretches and contractions [6] and another one that produces large torsions [11] using sixbar tensegrity and thin McKibben muscles [13]. Each module is realized by attaching 12 additional artificial muscles to the six-bar tensegrity structure.…”

A Novel Variable Stiffness Compound Extensor-Pneumatic Artificial Muscle (CE-PAM): Design and Mathematical Model

“…As the length of the sleeve in the extensor is double that of the bladder, the relation between the length of the extensor's thread (𝑏 𝑒 ) and the length of the contractor's thread ( 𝑏 𝑐 ) will be as in equation (6). The equation ( 7) can be used to calculate the number of turns of the extensor muscle from the contraction's turns and vice versa.…”

“…The Bridgestone Company produced the first commercial version of the pneumatic artificial muscle (PAM) [2]. It is used to construct soft robots with several bendable joints and a high degree of freedom, rather than rigid robots with discrete fixed joints [3][4][5][6][7]. These robots provide safer interactions with humans when directly in contact with their bodies [8][9][10][11][12].…”