摘要
基于仿生学中枢模式发生器(CPG)模型,在线规划机器人腿部前向运动关节辅助轨迹。利用基于信任度分配的小脑模型(CA-CMAC)算法建立运动调节映射机制,并且根据机器人传感反馈信息及环境参数的变化,调节CPG模型参数,实现环境自适应感知。以NAO机器人为实体研究对象,在斜坡试验环境中验证控制方法的有效性及可行性。
Based on central pattern generator（CPG） model, the auxiliary trajectories of robot＇ s leg joints are generated. Then, using the credit assignment-cerebella model articulation controller （CA-CMAC） algorithm,a motion adjustment mapping mechanism is established. According to the robot＇ s sensing feedback information and the changes of environmental parameters, CPG parameters are adjusted to realize the adaptive environmental perception. Taking the robot NAO as the research object, the feasibility and efficiency of the control method is validated in slope experimental environment.
出处
《系统仿真技术》
2017年第1期6-10,共5页
System Simulation Technology
关键词
双足机器人
中枢模式发生器(CPG)
小脑模型(CA-CMAC)
环境感知
biped robot
central pattern generator （CPG）
credit assignment-cerebella modelarticulation controller（CA-CMAC）
environmental perception
