基于中枢神经模式的四足机器人步态控制

Quadruped Robot Gait Control Based on Central Pattern Generator

为实现四足机器人稳定的节律性行走,研究基于中枢神经模式发生器(Central pattern generator,CPG)的比例步态控制方式。构建互抑神经元组成的振荡器模型,并基于振荡器模型组建四足机器人髋关节CPG网络。通过仿真研究得到模型各参数与CPG网络输出特性之间的关系,确定一套整定后CPG网络的模型参数,提出四足机器人比例步态,通过CPG模型阈值的调整可实现不同占空比的步态。对基于CPG网络的步态反射特性进行分析。试验表明,该方法可实现稳定的四足机器人行走,且具备一定的障碍物反射能力,具有较好的环境适应性。

To realize the stable and rhythmic walking of quadruped robot, proportion gait control strategy based on central pattern generator （CPG） is explored. The oscillator is modeled by two mutually inhibited neurons. Furthermore, quadruped hip joint CPG network is constructed on the basis of this kind of oscillator model. According to the simulated relation between oscillator parameters and output of the CPG network, a group of parameters of CPG network are determined and a proportion gait is proposed. Gait with different duty factor can be realized by threshold adjustment. The reflex characteristic of gait based CPG network is analyzed. Experiments show that the stable walking can be achieved through this control method based on CPG with good obstacle reflex performance and environmental adaptation.