基于卡尔曼滤波算法的机器人速度测量及优化

Robot Speed Measurement Based on Kalman Filtering Algorithm and the Optimization

根据机器人产品的质量和安全关注点,并结合国家机器人检测与评定中心的实际工作,分析了国内外机器人相关的标准,得出运动速度的测量是机器人检测评定过程中的重要项目。利用激光跟踪仪测量机器人运动速度的过程中存在误差,分析了误差的主要来源。为了减小误差,提出了基于卡尔曼滤波算法对测量数据进行滤波的方法。介绍了卡尔曼滤波算法的基本原理和主要流程,建立了机器人运动速度测量过程的状态方程和观测方程。最后,试验验证了卡尔曼滤波算法的滤波效果。试验结果表明,卡尔曼滤波算法可以将机器人运动速度的测量误差从17%降低到5%,有效地改善了测量结果。

According to the quality and security of the rubot product,combining with the practicc of national robot testing and evaluation center, this paper analyzed the relative standards of robot at home and abroad, and concluded that the measurement of movement velocity is an important project in the robot testing and evaluation process. There is an error in the process to track robot＇ s speed by using laser tracker. The paper＂ analyzed the main source of the error,that it is from the state of measurement apparatus and measured object. In order to reduce the error,the paper proposed an algorithm based on Kahnan filtering method to fiher the data. This paper＂ introduced the method＇ s principle and process, established the state equation and observation equation of robot speed measunement. Finally,the test was done to verify the effect of Kahnan filtering, and the results show that the Kalman filrering algorithm can reduce the measurement error from 17% to 5% , which improves the measurement results effectively.