学习人类控制策略的双足机器人步态控制研究  

Research of biped robot' s walking gait control based on learning human

作　　者：何志[1] 谭建豪[1] 

机构地区：[1]湖南大学电气与信息工程学院控制科学与工程系,长沙410082

出　　处：《计算机工程与应用》2014年第5期234-238,共5页Computer Engineering and Applications

基　　金：湖南省自然科学基金重点项目(No.08JJ3132)

摘　　要：针对双足机器人面临的复杂环境下动态行走的适应性难题,提出了一种基于学习人类控制策略的双足机器人步态控制方法。利用三维线性倒立摆模型构造双足行走系统的状态方程,建立学习人类控制策略的参数化模型,设计了基于SVM的学习型控制器。该方法保证了躯干始终处于与地面近似垂直,增强了步态控制的鲁棒性,提高了双足机器人在复杂环境下行走的动态稳定性。实验验证了该方法的有效性。To deal with the dynamically walking control problem in the complex environments for biped robot, a method of gait control based on learning human control strategy is put forward. State equation of biped walking system based on 3D linear inverted pendulum is constructed. The parametric model of learning HCS is built. A learning controller based on SVM is designed. The proposed method guarantees that torso is always perpendicular to the ground. Robustness of the gait control is enhanced. The dynamically stability of biped walking is improved in complex environments. Experimental results demonstrate the effectiveness of the proposed methods.

关 键 词：双足机器人 步态控制 支持向量机(SVM) 人类控制策略 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]