The tip asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. This enables robotic needle steering, which can be used in medical procedures to reach subsurface targets inaccessible by straight-line trajectories. However, accurate path planning and control of needle steering require models of needle-tissue interaction. Previous kinematic models required empirical observations of each needle and tissue combination in order to fit model parameters. This study describes a mechanics-based model of robotic needle steering, which can be used to predict needle behavior and optimize system design based on fundamental mechanical and geometrical properties of the needle and tissue. We first present an analytical model for the loads developed at the tip, based on the geometry of the bevel edge and material properties of soft-tissue simulants (gels). We then present a mechanics-based model that calculates the deflection of a bevel-tipped needle inserted through a soft elastic medium. The model design is guided by microscopic observations of needle-gel interactions. The energy-based formulation incorporates tissue-specific parameters, and the geometry and material properties of the needle. Simulation results follow similar trends (deflection and radius of curvature) to those observed in experimental studies of robotic needle insertion.

中文翻译：

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机器人通过软组织引导的柔性针的力学

斜尖针头的针尖不对称导致针头在插入软组织时自然弯曲。这使机器人针转向，可用于医疗程序，以到达直线轨迹无法到达的地下目标。然而，精确的路径规划和针转向控制需要针与组织相互作用的模型。以前的运动学模型需要对每个针和组织组合进行经验观察，以便拟合模型参数。本研究描述了一种基于力学的机器人针头转向模型，该模型可用于预测针头行为并基于针头和组织的基本机械和几何特性优化系统设计。我们首先提出了在尖端产生的载荷的分析模型，基于斜边的几何形状和软组织模拟物（凝胶）的材料特性。然后，我们提出了一个基于力学的模型，用于计算插入软弹性介质的斜尖针的偏转。模型设计以针-凝胶相互作用的显微观察为指导。基于能量的配方结合了组织特定参数以及针的几何形状和材料特性。模拟结果遵循与机器人针插入实验研究中观察到的相似趋势（偏转和曲率半径）。基于能量的配方结合了组织特定参数以及针的几何形状和材料特性。模拟结果遵循与机器人针插入实验研究中观察到的相似趋势（偏转和曲率半径）。基于能量的配方结合了组织特定参数以及针的几何形状和材料特性。模拟结果遵循与机器人针插入实验研究中观察到的相似趋势（偏转和曲率半径）。