Force feedback time prediction based on neural network of MIS Robot with time delay

Yi Ning, Lili Han, Zhao Xiao, Baoguo Liu
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引用次数: 1

Abstract

Robotic technology is enhancing surgery through improved precision, stability, and dexterity. In manual MIS, the surgeon is separated from the operation area, which is reached by long instruments. In image-guided procedures, image prediction technique based on visual reality technology has solved time-delay problem of image information between master and slave manipulator of teleoperation system effectively in many application fields. However, time-delay of force feedback information which is transmitted from communication link is also inconvenient to the operator's working and makes a bad influences on the system's stability and transparency. In this paper, the start and stop time of feedback force torque can be predicted by using RBF neural network technology when the slave manipulator is interacting with the environment, such that the force feedback information can synchronize with the predictive image. Simulation results show excellence of the proposed scheme.
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基于神经网络的时滞MIS机器人力反馈时间预测
机器人技术通过提高精确性、稳定性和灵活性,正在加强外科手术。在手动MIS中,外科医生与手术区分开,手术区是通过长器械到达的。在图像引导过程中,基于视觉现实技术的图像预测技术在许多应用领域有效地解决了遥操作系统主从机械手之间图像信息的时滞问题。然而,从通信链路传输的力反馈信息的时滞性也给操作者的工作带来不便,对系统的稳定性和透明性产生不利影响。本文利用RBF神经网络技术预测从机与环境交互作用时反馈力转矩的起、停时间,使力反馈信息与预测图像同步。仿真结果表明了该方案的优越性。
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