基于MSVR的六维腕力传感器静态解耦算法

Static Decoupling Algorithm of Six-Axis Wrist Force Sensor Based on Multi-output Support Vector Regression

针对维间耦合会影响六维腕力传感器测量精度的问题,提出了基于多输出支持向量回归机(Multi-output support vector regression,MSVR)的解耦算法。以实验室研制的六维腕力传感器为例进行静态标定实验,使用基于MSVR的解耦算法以及传统的基于最小二乘求解标定矩阵的解耦算法对标定数据进行处理分析。实验结果表明,本文提出的解耦算法稳定可靠,能有效抑制维间耦合的干扰,具有较高的解耦精度。

As the measurement accuracy of six-axis wrist force sensor is affected by interdimensional coupling,a decoupling algorithm based on multi-output support vector regression(MSVR)is proposed.The static calibration experiment is carried out on the six-axis wrist force sensor designed by the lab,and the data processing and analysis are proceeded both on the decoupling algorithm based on MSVR and the traditional decoupling algorithm based on least square theory solving calibration matrix.Experimental results show that the decoupling algorithm proposed in this paper has features of stability,high reliability and high precision,and can effectively inhibit interdimensional coupling interference.