中文摘要：

风电叶片爬壁机器人的曲面爬行步态是研究难点。为此建立了含3个T型和2个I型关节的5自由度仿尺蠖机器人机构模型;通过几何关系分析机构对球曲面的适应性,基于吸附稳定状态建立关节角度幅值与曲率半径之间的函数关系,采用余弦函数设计翻转步态轨迹;基于反馈学习方法、自适应频率Hopf振荡器和Kuramoto耦合,设计关节中枢模式发生器（CPG）单元及其网络;通过学习平面翻转步态得到CPG网络参数初值,再通过在线调节关节角度幅值规划球曲面翻转步态。通过Matlab和Adams联合仿真分析了CPG网络的稳定性;进行了实物样机测试,测试了在叶片曲面上的翻转步态。研究结果表明,利用吸附稳定所需角度幅值可将平面步态调节为曲面步态,CPG在线调节步态规划方法有效。

英文摘要：

The curved surface climbing gait is the key of wall-climbing robots for detecting the wind turbine blades. A mechanical model of an inchworm-like climbing robot with 5 DOF is designed,including three T type joints and two I type joints. The adaptability of the vacuum sucker and mechanical model to the arc surface is analyzed based on geometric method. The fliping gaits on curved surface are analyzed by the circular trajectory planning method. The function relationship between the joint angle and curvature radius is established based on the stable adsorption state. Based on the supervised learning method,the adaptive frequency Hopf oscillator and Kuramoto couple,a central pattern generator（ CPG） module corresponding to a joint and a CPG network of robot are designed. The steady-state values of the parameters which are learned from the flat flip gait can be the initial values of the parameters of CPG network,and then the flip gait on curved surface is planned by adjusting the angle amplitudes online. The coordinated simulation of the curved surface flip gait based on Matlab and Adams is carried out,which validates the stability of the proposed CPG network. The physical prototype robot is developed,and the flip gait ex-periments on curved surface are carried out. The results show that the angle amplitude gained from the stable adsorbing status can be used to transfer the plane gait to curved surface gait,and the online adjustment CPG planning is valid.