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Research on Walking Gait of Biped Robot Based on a Modified CPG Model

机译:基于改进的CPG模型的两足机器人步行步态的研究

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The neurophysiological studies of animals locomotion have verified that the fundamental rhythmic movements of animals are generated by the central pattern generator (CPG). Many CPG models have been proposed by scientific researchers. In this paper, a modified CPG model whose output function issin(x)is presented. The paper proves that the modified model has stable periodic solution and characteristics of the rhythmic movement using the Lyapunov judgement theorem and the phase diagram. A modified locomotion model is established in which the credit-assignment cerebellar model articulation controller (CA-CMAC) algorithm is used to realize the pattern mapping between the CPG output and the musculoskeletal system. And a seven-link biped robot is employed to simulate cyclic walking gait in order to test the validity of the locomotion model. The main findings include the following. (1) The modified CPG model can generate spontaneous oscillations which correspond to biological signals. (2) The analysis of the modified locomotion model reveals that the CA-CMAC algorithm can be used to realize the pattern mapping between the CPG output and the musculoskeletal system.
机译:动物运动的神经生理学研究证实,动物的基本节律运动是由中央模式发生器(CPG)产生的。科研人员已经提出了许多CPG模型。本文提出了一种改进的CPG模型,其输出函数为sin(x)。利用Lyapunov判断定理和相图证明了改进的模型具有稳定的周期解和节奏运动的特征。建立了改进的运动模型,其中使用信用分配小脑模型关节控制器(CA-CMAC)算法来实现CPG输出与肌肉骨骼系统之间的模式映射。为了验证运动模型的有效性,还使用了一个七链双足机器人来模拟周期性步行步态。主要发现包括以下内容。 (1)修改后的CPG模型可以产生与生物信号相对应的自发振荡。 (2)对改进的运动模型的分析表明,CA-CMAC算法可用于实现CPG输出与肌肉骨骼系统之间的模式映射。

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