Research pathways from tensegrity-related biological structures to tensegrity robots: a bibliometric analysis

摘要

Tensegrity describes a structural principle featuring a self-stabilizing system that consists of continuous tension elements and discontinuous compression elements. This paper undertakes a comprehensive systematic review of the overall development status and defining characteristics of the tensegrity field, employing bibliometric analysis methods and adopting an evolutionary perspective. Based on data spanning a 35 year period on the tensegrity theme sourced from the Web of Science database, we conducted detailed analyses of annual publication trends, significant authors, research areas, journals and co-occurrence maps of author keywords. These analyses collectively provide a nuanced description of the current state of the tensegrity field, as well as two pivotal sub-fields: biotensegrity and tensegrity robots. Through an analysis of research keywords and a timeline of evolving research hotspots within the tensegrity field, we have discerned a continuous evolution in the primary research focuses; from the initial conceptual application of tensegrity in the biological domain, to the subsequent refinement and development of tensegrity theory, and finally to ongoing advancements in tensegrity robots. From an evolutionary perspective, the dynamic transitions of research hotspots in tensegrity studies reflect both the field's progressive maturation and its expansion into emerging research frontiers. In addition, bioinspiration focuses on abstracting principles from nature to inspire novel solutions in other fields or sub-fields. Tensegrity structures exhibit explanatory compatibility with biological architectures. Based on this, the biotensegrity and tensegrity robots each belong to two bioinspiration pathways within the tensegrity framework. Tensegrity robots have emerged as the most prominent research sub-field within the broader conceptual framework of tensegrity, exhibiting a steadily increasing share of publications in the overall tensegrity literature. However, tensegrity robots still face a series of fundamental challenges, including the complexity of dynamic modeling and control, as well as the dilemma in structural optimization. Addressing these issues will likely depend on (1) improved theoretical models of tensegrity systems, (2) specialized tensegrity models tailored to different bio-inspired prototypes, and (3) novel integrations with various control methodologies. These directions are expected to remain key research focuses in the coming years.