摘要
基于对生物节律性周期运动的CPG控制的概念,采用Lakshmanan和Murali的双变量简化Hodgkin-Huxley振荡神经元模型作为CPG的振子。对该模型进行了不动点及稳定性分析和分岔分析,指出了其二次Hopf分岔特性和振荡条件。在此基础上,建立了一种用于八足步行机器人步态控制的CPG模型。通过分阶段遗传算法,分别针对几种步态进行了参数优化,通过仿真验证了所提出的CPG模型的可行性。
Based on the anatomy fact that the rhythmic motor pattern is controlled by CPG function modular, the conception of CPG control in multi-legged gait is presented. Neuraxon' s nonlinear oscillation model given by Lakshmanan and Murali is analyzed, Hopf bifurcation phenomenon and effects of parameters on its oscillation behavior are discussed. A CPG model for multi-legged walking robot' s gait control is made by adopting the neuron oscillator, parameters of the model is optimized by using multi-stage genetic algorithm and some gaits are generated using this model by simulation. Simulation result proved the constructed CPG model is feasible.
出处
《制造业自动化》
北大核心
2007年第10期34-39,共6页
Manufacturing Automation