Bio-inspired control of lower limb exoskeleton using a central pattern generator

【摘要】：This paper,we present a new framework for lower extremity exoskeleton to generate on-line trajectory and get in sync with the environment based on a simplified neural-skeletal–muscle system.In contrast to non-autonomous movement representations like splines,because of the introduction of the concept of central pattern generator(CPG) in biology,this system is autonomous dynamical system,i.e.a system of differential equations with at least one limit cycle attractor.This neural-skeletal–muscle system consists of 7 segments and 18 virtual muscles,and controlled by a CPG network composed of 6 pair of neural oscillators,and mechanisms for processing and transporting sensory and motor signals.We evaluate the system with a humanoid robot simulation and an actual lower limb exoskeleton.Through the test,we found that locomotion emerged as a stable limit cycle that was generated by the global entrainment between the skeletal–muscle system,the neural system,and the environment.