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Real-time enhancement of tracking performances for cable-conduit mechanisms-driven flexible robots

机译:实时增强电缆导管机制驱动的柔性机器人的跟踪性能

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Natural Orifice Transluminal Endoscopic Surgery (NOTES) is a method that allows for performing complex operations via natural orifices without skin incisions. Its main tool is a flexible endoscope. Cable-conduit mechanism (CCM) or tendon-sheath Mechanism (TSM) is often used in NOTES because of its simplicity, safety in design, and easy transmission. Nonlinearities between the cable and the conduit pose challenges in the motion control of the NOTES system. It is very difficult to achieve the precise position of robotic arms when the system is inside a human's body. This paper presents new approaches to model and control a pair of CCMs (TSMs) used in NOTES system. To deal with the change of cable-conduit configurations during its operation, two control schemes are proposed: (ⅰ) an updated table with offline backlash hysteresis learning is constructed. In this case, a simple computation of the direct inverse backlash hysteresis model is introduced without using output feedback for compensation; and (ⅱ) an online estimation of the backlash hysteresis profile under the assumption of availability of output feedback. In this case, adaptive control laws are used to deal with the change of the endoscope configuration. The proposed model and compensation control schemes are experimentally validated using a prototype of a single-DOF-Master-Slave system, which consists of a master console, a telesurgical workstation, and a slave manipulator. The results show that the proposed model and the control schemes improve the tracking performances of the system.
机译:天然孔腔内镜手术(NOTES)是一种无需皮肤切口即可通过天然孔进行复杂手术的方法。它的主要工具是柔性内窥镜。 NOTES中经常使用电缆导管机制(CCM)或腱鞘机制(TSM),因为它简单,设计安全且易于传输。电缆和导管之间的非线性对NOTES系统的运动控制提出了挑战。当系统位于人体内部时,很难实现机械臂的精确位置。本文介绍了用于建模和控制NOTES系统中使用的一对CCM(TSM)的新方法。为了应对电缆导管配置在其运行期间的变化,提出了两种控制方案:(ⅰ)构造了具有离线背隙磁滞学习功能的更新表。在这种情况下,无需使用输出反馈进行补偿即可引入直接反冲间隙滞后模型的简单计算。 (ⅱ)在有输出反馈可用性的前提下,对背隙磁滞曲线进行在线估计。在这种情况下,自适应控制法则用于处理内窥镜配置的变化。所提出的模型和补偿控制方案通过使用单DOF主从系统的原型进行实验验证,该系统由主控制台,远程手术工作站和从机组成。结果表明,所提出的模型和控制方案提高了系统的跟踪性能。

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