Large Language Model-empowered multimodal strain sensory system for shape recognition, monitoring, and human interaction of tensegrity

Abstract-- A tensegrity-based system is a promising approach for dynamic exploration of uneven and unpredictable environments, particularly, space exploration. However, implementing such systems presents challenges in terms of intelligent aspects: state recognition, wireless monitoring, human interaction, and smart analyzing and advising function. Here, we introduce a 6-strut tensegrity integrate with 24 multimodal strain sensors by leveraging both deep learning model and large language models to realize smart tensegrity. Using conductive flexible tendons assisted by long short-term memory model, the tensegrity achieves the self-shape reconstruction without extern sensors. Finally, human interaction system of the tensegrity helps human obtain necessary information of tensegrity from the aspect of human language. The concept of using tensegrity structures in space exploration is an innovative approach that offers several advantages due to the unique properties of tensegrity systems. One famous example is the "Super Ball Bot" developed by NASA (National Aeronautics and Space Administration) [1][2]. Tensegrity structures are composed of solid compression components (rods/struts) connected by tension elements (cables/strings).