Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data.
Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data.
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DOI：
10.1109/tmech.2012.2209673
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发表时间：
2013-10-01
期刊：
影响因子：
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通讯作者：
Cavuşoğlu MC
中科院分区：
文献类型：
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作者：
Boonvisut P;Cavuşoğlu MC
用于机器人手术系统中的任务自动化的机器人运动规划算法依赖于目标软组织变形的精确模型的可用性。在构建组织变形模型时依赖通用组织参数是有问题的，因为已知生物组织具有非常大的（受试者间和受试者内）变异性。在外科手术之前对目标组织进行先验机械表征（例如单轴台架测试）通常也是不切实际的。本文提出了一种根据机器人手术操作过程中收集的感知数据估计软组织机械参数的方法。该方法使用从安装在机器人操纵器上的多轴力传感器收集的力数据以及从立体摄像机系统收集的组织变形数据。然后使用逆有限元方法估计组织参数。在仿真中分析了测量和建模不确定性对所提出方法的影响。还给出了该方法的实验评估结果。
Robotic motion planning algorithms used for task automation in robotic surgical systems rely on availability of accurate models of target soft tissue’s deformation. Relying on generic tissue parameters in constructing the tissue deformation models is problematic because, biological tissues are known to have very large (inter- and intra-subject) variability. A priori mechanical characterization (e.g., uniaxial bench test) of the target tissues before a surgical procedure is also not usually practical. In this paper, a method for estimating mechanical parameters of soft tissue from sensory data collected during robotic surgical manipulation is presented. The method uses force data collected from a multiaxial force sensor mounted on the robotic manipulator, and tissue deformation data collected from a stereo camera system. The tissue parameters are then estimated using an inverse finite element method. The effects of measurement and modeling uncertainties on the proposed method are analyzed in simulation. The results of experimental evaluation of the method are also presented.