Meta-Network Architecture: A Paradigm Shift in Evolutionary Biomechanics and Robotic Control

This paper introduces the Meta-Network Architecture as a new paradigm in biomechanics and robotic control, based on the foundational theory of Kinegenesis and the methodology of Formless Flow. Unlike the traditional kinetic chain model, which represents the body as a sequence of rigid segments, the Meta-Network describes movement as an emergent property of a dynamically reconfigurable system organized across multiple scales. At its core is the Axial Wave — a three-dimensional helical propagation through the body enabled by Maximum Dynamic Relaxation (MDR), allowing continuous force transmission, reduced energy loss, and self-organizing motion. The Meta-Network operates through state regulation and topological reconfiguration (node opening and blocking), producing non-linear movement outcomes from identical initial impulses. An evolutionary framework is proposed, integrating functional layers from amoeba-like undulatory organization to advanced limb coordination in mammals and apes. The implications extend to artificial intelligence and robotics, suggesting a shift from trajectory-based control to state-driven morphological intelligence, enabling adaptive, energy-efficient, and low-latency systems. This work proposes a transition from control of movement to organization of conditions for movement, offering a foundation for next-generation biomechanical models and robotic architectures.