中文摘要：

为了改进机器人磨削过程中对磨削量的控制，提出了一种基于SVM回归的磨削过程建模方法，通过分析与磨削量相关的一组可测变量——机器人进给速率、接触力、工件表面曲率，利用机器学习的方法建立回归模型，对磨削量进行预测．这种方法可以避免逐一分析复杂的动力学参数．实验结果表明，该方法可以取得良好的效果，模型的预测精度达到90％以上，基本满足实际加工的要求．

英文摘要：

To improve the removal control for robot grinding process, we propose a modeling method based on SVM （support vector machine） regression. By analyzing a group of measurable variables relevant to grinding removal, such as robot＇s speed, contact force and curvature of the workpiece＇s surface, a regression model is built using machine learning method to predict the grinding removal. In this way, the analysis on a series of complicated dynamic variables could be avoided. The experimental results show that this method could achieve good performance. The prediction accuracy of the model reaches higher than 90%, which basically meets the demand of practical grinding.