| It has always been one of the hotspots in the research field of quadruped robots to enable quadruped robots to have the controllability of stable rhythmic motion,similar to the process of “never walk to walk” of quadrupeds.Modern neurophysiological research has shown that the process of “never walk to gain rhythmic gait motion ability” of quadrupeds is mainly caused by the development of the synapses of each nerve in the central loop network under the continuous evaluation and guidance of external information.Therefore,the establishment of a central loop network model,similar to the mechanism of synaptic development of quadrupeds has become one of the keys to realize the goal of “never walks to can walk” of quadruped robots.However,the current modeling research on the central loop network find it difficult to give a quadruped robot the ability of “never walk to walk”,resulting of the ignorance of the developmental characteristics of the central loop.Modern biological behavior studies have found that the rhythmic gait motion controllability of quadrupeds is not innate,but gradually formed in a period of time after birth.For example,the small gazelle cannot even stand when it is just born,but can stand and perform small-range static gait motion after tens of minutes,obtaining rhythmic motion ability in a few hours.The process of "never walks to walk" of this kind of quadrupeds is mainly caused by the development of the synapses of each nerve in the central loop network under the continuous evaluation and guidance of external information,the detail of which is: the random development of nerve synapses→the initial formation of the central loop network→generation of random small-range motions→evaluation of each synapse in the network→guidance of the corrective development of each synapse in the network→continuously expansion of the range of motion→until the central loop network meets the needs of rhythmic motion control.Targeting at the current quadruped robot’s need to realize the rhythmic gait motion controllability of "never walks to walk" and the deficiencies in the res earch of the central loop network model,this article draws on the initial developmental process of biological motion control nervous system(central loop network)and the vibration characteristics of synaptic electrical signals,combined with the effect o f synaptic physical characteristics on signal transmission of nerve cell and the evaluation of the effect on the corrective development of the central loop network,establishing a neural network synapse fertility model.In addition,experiments through a quadruped robot are implemented to test the accuracy and effectiveness of the model and method established in this article.First,focusing on the problem of the separation of the microscopic and macroscopic characteristics of nerve cells in the current neu ral cell electrical signal vibration model,this article starts from the concentration fluctuation of potassium and sodium ion,using the macroscopic characteristics of nerve cell electrical signal vibration,establishing a neural cell electrical signal vi bration model.Then combined with the characteristic analysis of the electrophysiological experiment of the nerve cell electrical signal,the stability,the existence of the periodic solution,the relaxation vibration and the chaos of the established nerve cell electrical signal vibration model are studied,as well as the corresponding parameter range is obtained.Moreover,a comparative experiment on the vibration response of the built model and the motor nerve of an annelid mollusk is carried out.The exp erimental results show that the established nerve cell electrical signal vibration model can well describe the electrical signal vibration characteristics of biological motor nerve cells.Secondly,starting from the perspective of biological neurodevelopme nt,combining the directionality and randomness of synaptic development,based on the analysis of the physical equivalence of synaptic development characteristics and stochastic dynamics and the analysis of synaptic development characteristics,the developmental model of synapse is established,including: synaptic growth direction guidance model based on gravitational field,synaptic growth equation,synaptic random steering model,and synaptic corrective development model.Then,synaptic growth simulation experiments were carried out,whose results were analyzed.From the analysis,it is shown that the established synaptic breeding model is correct and effective.Once again,by simplifying the synaptic equivalent cable model proposed by Lahr,the synaptic path transfer function is established.By analyzing the characteristics of the transfer function,the time constant of the transfer function is obtained.Based on the analysis of the duty ratio,movement speed,and coordinated relationship of legs of quadrupeds,with the fusion of movement speed,duty ratio and phase difference,a synaptic development network evaluation algorithm is established.A synaptic development network simulation experiment is carried out,whose results show the accuracy and effectiveness of established model and algorithm.Finally,in order to verify the effectiveness of the above established models and algorithms,the quadruped robot simulation platform was used to develop and optimize the developmental neural network,on which robot motion control experiment was carried out to verify that the developmental neural network model and network evaluation algorithm can realize the motion control process of “never walk to walk” of the quadruped robot.On this basis,by using the half-moon-legged quadruped robot platform,it is further verified that the developmental neural network model and network evaluation algorithm are able to realize that the process of “never walk to know how to walk” of quadruped robot.Then,the hydraulically driven quadruped robot platform was used to carry out a comparative experiment on control walking,compared with the Matsuoka central loop model,which verifies that the established developmental network has a better effect on the motion control of the hydraulically driven quadruped robot platform. |
