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首页> 外文期刊>IEEE Robotics and Automation Letters >Dual-Arm Robotic Needle Insertion With Active Tissue Deformation for Autonomous Suturing
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Dual-Arm Robotic Needle Insertion With Active Tissue Deformation for Autonomous Suturing

机译:具有主动组织变形功能的双手臂机器人针头可自主缝合

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摘要

A major issue for needle insertion into soft tissue during suturing is the induced tissue deformation that hinders the minimization of tip-target positioning error. In this letter, we present a new robot control framework to solve target deviation by integrating active deformation control. We characterize the motion behavior of the desired target under needle-tissue interaction by introducing the needle-induced deformation matrix. Note that the modeling does not require the exact knowledge of tissue or needle insertion properties. The unknown parameters are online updated during the insertion procedure by an adaptive estimator via sensor-based measurement. A closed-loop controller is then proposed for dualarm robotic execution upon image guidance. The dual-arm control aims to regulate a feature vector concerning the tip-target alignment to ensure target reachability. The feasibility of the proposed algorithm is studied via simulations and experiments on different biological tissues to simulate robotic minimally-invasive suturing using the da Vinci Research Kit as the control platform.
机译:在缝合过程中,针头插入软组织的主要问题是引起的组织变形,阻碍了尖端目标定位误差的最小化。在这封信中,我们提出了一个新的机器人控制框架,通过集成主动变形控制来解决目标偏差。我们通过引入针头诱导的变形矩阵来表征所需目标在针头组织相互作用下的运动行为。请注意,建模不需要了解组织或针头插入属性的确切知识。未知参数在插入过程中由自适应估计器通过基于传感器的测量进行在线更新。然后提出一种闭环控制器,用于在图像引导下执行双臂机器人。双臂控制的目的是调节与尖端-目标对准有关的特征向量,以确保目标可达性。通过以达芬奇研究工具包为控制平台,对不同生物组织进行模拟微创缝合的模拟和实验,研究了该算法的可行性。

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