Soft Tensegrity Robot Driven by Thin Artificial Muscles for the Exploration of Unknown Spatial Configurations

• Published in: IEEE robotics and automation letters Vol. 7; no. 2; pp. 5349 - 5356
• Main Authors: Kobayashi, Ryota, Nabae, Hiroyuki, Endo, Gen, Suzumori, Koichi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-04-2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial muscles; Deformation; Muscles; Recurrent neural networks; Robot sensing systems; Robots; Rubber; Shape; Shape recognition; Soft robot applications; Soft robotics; soft sensors and actuators; Strain; tensegrity structure; Tensegrity structures; thin McKibben muscle; three-dimensional environment recognition; Windings
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2022.3153700

The primary role of a robot exploring an unknown space is to investigate the state and the spatial shape of the environment. We have designed a soft robot that aims to move forward in an unknown space as it recognizes and adapts to the spatial shape of the environment. We previously reported that soft tensegrity and recurrent neural network can be used to realize tensegrity structure shape recognition. In this study, a tensegrity robot was designed to actively generate propulsive force as it presses its body against a wall in its surrounding environment. This robot design includes a novel artificial muscle arrangement called "4/3 muscle winding," which induces large deformation in the tensegrity structure. The application of this new artificial muscle arrangement allows two types of large deformations to be induced in the tensegrity structure, which results in displacements of 20% to 40% in the axial and radial directions. We have demonstrated that the robot, which was created by connecting the tensegrity structures, is lightweight and possesses passive shape adaptability in a three-dimensional environment. This tensegrity robot could enter an unknown space, such as a cave, and recognize the spatial shape of the surrounding environment by recognizing the tensegrity structure shape.