于凌涛, 王文杰. 基于系统阻力变化的手术微器械夹持力检测[J]. 机器人, 2018, 40(3): 368-376. DOI: 10.13973/j.cnki.robot.170401
引用本文: 于凌涛, 王文杰. 基于系统阻力变化的手术微器械夹持力检测[J]. 机器人, 2018, 40(3): 368-376. DOI: 10.13973/j.cnki.robot.170401
YU Lingtao, WANG Wenjie. Clamping Force Sensing of Surgical MicromanipulatorsBased on the Changes of System Resistance[J]. ROBOT, 2018, 40(3): 368-376. DOI: 10.13973/j.cnki.robot.170401
Citation: YU Lingtao, WANG Wenjie. Clamping Force Sensing of Surgical MicromanipulatorsBased on the Changes of System Resistance[J]. ROBOT, 2018, 40(3): 368-376. DOI: 10.13973/j.cnki.robot.170401

基于系统阻力变化的手术微器械夹持力检测

Clamping Force Sensing of Surgical MicromanipulatorsBased on the Changes of System Resistance

  • 摘要: 针对手术机器人微器械的力检测问题,搭建了3自由度微器械的等效实验平台.基于柔索驱动微器械关节完整的动力学模型设计了驱动关节综合阻力模型,并根据实验结果进行了BP (反向传播)神经网络模型的数据拟合,给出综合阻力神经网络模型.最后根据驱动单元综合阻力的变化提出了一种夹持力估计策略,并通过连续加载和阶梯加载实验验证了夹持力检测方法的性能.实验结果显示,夹持力检测的最大绝对误差可以达到0.24 N,在稳定阶段夹持力检测的精度可以达到90%左右.该方法可以成为实现手术机器人微器械力反馈的基础.

     

    Abstract: An equivalent experimental platform for a 3 DOF (degree of freedom) micromanipulator is established to solve the force sensing problem for surgical robot micromanipulator. A comprehensive resistance model of the driven joint unit is designed based on the complete dynamic models of the cable-driven micromanipulator joints, and the comprehensive resistance neural network model is obtained through data fitting of the experimental results based on BP (backpropagation) neural network model. Finally, a clamping force estimation strategy is proposed based on the comprehensive resistance changes of the driven unit, and its performance is verified by the experiments of continuous and stepped clamping force loading. The experiment results show that the maximum absolute error is 0.24 N in clamping force measurement, and the accuracy can reach up to 90% in stable period. The method lays the foundation for realizing force feedback of the surgical robot micromanipulator.

     

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