一种Stewart结构六维力/力矩传感器参数辨识研究

介绍了一种大量程Stewart结构六维力/力矩传感器系统.建立了传感器力/力矩测量数学模型,构建了基于运动学逆解的优化目标函数.提出了一种新的参数标定法,称作分支轮换标定法.基于所研发的六维力/力矩传感器系统进行了实验研究,实验结果表明分支轮换法可以有效地辨识出传感器的结构参数,提高了测量精度.该方法可用于类似结构的六维力/力矩传感器参数标定.

This paper presents a large-scale Stewart platform-based six-component force/torque sensor.A force/torque measurement model is established and an optimal objective function based on the inverse kinematics is offered.A novel parameter calibration method,named branch-in-turn calibration,is presented.Based on the developed prototype of the six-component force/torque sensor,experiments have been made.The experimental results show that the branch-in-turn calibration method can effectively identify the structural parameters of the sensor and the measurement accuracy is improved. This method can be applied to parameter calibration of the six-component force/torque sensor with similar structure.