【作者】 谢成清；

【导师】 夏洪；

【作者基本信息】 东华理工大学 ， 电路与系统， 2012， 硕士

【摘要】 本文以图像处理算法与滑模变结构控制理论为基础，选取机械手及乒乓球作为研究对象，并且开发了一个用C++语言编写的图像分割技术与伺服控制系统软件。为了实现机器人具有能够根据视觉信息抓取目标的能力，需要从摄像机获取的二维图像中提取出目标特征,但是所获取的图像受到不均匀光线的干扰，导致图像轮廓出现断裂等现象，从而影响到对目标特征识别的效果，进而导致视觉伺服系统在现实的环境中表现不佳等问题。针对这一问题，本文采用了滤波法去除干扰，并且尝试使用支持向量机方法对图像进行分割处理。支持向量机能够对非线性图像数据进行有效地分类，因此非常适合应用于分割机器人视觉系统中的目标图像。本文采用支持向量机方法对目标图像数据进行分类，实验结果表明：只要适当地选择样本量、样本特征，则该方法就能够有效地分割边界模糊、灰度不均匀等情况下的目标图像，并且克服了依靠大量实验来确定分割阈值的不确定性问题。针对机械手的建模误差及不确定性问题，本文结合了机器人常用的滑模变结构控制方法，以及分析了变结构中存在的抖振问题，并对机械手的运动轨迹进行了跟踪仿真研究。在此基础上，提出了一种径向基函数神经网络(Radical Basis Function NeuralNetwork)与基于名义模型的滑模变结构控制方法来削弱滑动模态在控制机械手运动中存在的抖振，并利用李亚普诺夫函数方法分析机械手运动的稳定性，仿真结果验证了该方法是可行的。更多还原

【Abstract】 This paper is based on the image processing algorithm and sliding mode variablestructure control theory, and choose mechanical arm and ping-pong as the research object,working out a software programme for image segmentation technology and servo controlsystem by VC. To realize the robot has able to grab target according to visual information,which is need to extract features of the target from2d image from camera, but the imagewas disturbed from the uneven light, leading to outline of the image appear rupturephenomenon, which influence recognition effect of the target feature, finally, this will leadto poor performance of visual servo system in the real environment. Pointing to theproblem, filtering methods have been input to remove interference and try to use thesupport vector machine method to do image processing in this paper.SVM (support vector machine) has able to classify nonlinear image data effectively,which is very suitable to segment target image of the robot visual system. This paper usingsupport vector machine classify image data of the target, the experimental results show thatif only choose appropriate sample size and feature, this method has able to segment targetimage with fuzzy boundaries and gray uneven, and overcome uncertainty problems thatrely on extensive experiments to determine segmentation thresholds.As for the modeling error and uncertain problems in the manipulator, this papercombines the sliding mode variable structure control method that often application forrobot, and analyzes chattering problem which existing in the variable structure, and carryon simulation research to trajectory of the manipulator. The paper extended it into a slidingmode variable structure control method based on the radial Basis Function Neural Networkand the name model to weaken chattering when sliding mode control manipulatormovement and analysis the stability of the manipulator movement by the Lyapunovfunction, and the simulation results verify that the method is feasible.更多还原