基于Kimura神经元振荡器的六足仿生机器人步态控制研究

Gait control for bio-inspired hexapod robot based on Kimura neural oscillator

生物中枢模式发生器(CPG)对六足机器人的步态控制具有重大研究意义,为此提出一种基于Kimura神经元振荡器的六足机器人CPG步态控制方法。首先,以蜘蛛为仿生对象设计六足机器人机械结构并对其进行运动学解算;然后,基于Kimura神经元振荡器建立振荡器模型并对其参数整定;其次,针对机器人6条单腿的相位关系设计CPG网络模型;最后,通过计算机仿真工具和样机进行联合实验。结果表明,基于Kimura神经元振荡器生成的CPG网络模型输出信号幅值和相位差稳定,能够满足六足机器人步态控制需求,为六足机器人的步态控制提供一种可行性方案。

Biological central pattern generator(CPG)is of great research significance to the gait control for hexapod robot.Therefore,a Kimura neural oscillator based CPG gait control strategy for hexapod robot is proposed.The mechanical structure of hexapod robot is designed with the spider as the bionic object,and its kinematics is solved.An oscillator model is established based on Kimura neural oscillator,and its parameters are adjusted.The CPG network model is designed according to the phase relation of the 6 legs of the robot.Gait experiments are conducted with computer simulation tools and prototypes.The results demonstrate that the output signal amplitude and phase difference of the CPG network model generated based on Kimura neural oscillator are stable,meeting the gait control requirements of hexapod robot.The study provides a feasible gait control strategy for hexapod robot.