基于参数自主选择模型的手术机器人绳驱动微机械臂位置估计器设计

IF 2.2 4区 计算机科学 Q2 ENGINEERING, MECHANICAL
Wenjie Wang, Jie Wang, Congcong Chen, Yang Luo, Xiaohua Wang, Lingtao Yu
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引用次数: 0

摘要

由于手术机器人的微机械臂工作空间狭窄,末端很难安装任何位置传感器,因此无法准确地进行位置控制和位置检测。提出了一种基于参数自主选择模型的位置估计器,用于间接估计末端位置。首先,通过微机械臂的四自由度驱动方案和索驱动模型,建立了单关节原理原型和位置估计器模型;其次,将提出的参数变化模型与参数选择方法相结合,形成参数自主选择模型;最后,建立了基于参数自主选择模型的位置估计器。实验结果表明,该位置估计器的最大估计误差为0.1928°。与其他位置估计方法相比,本文提出的位置估计器具有更高的精度和更好的鲁棒性,为微机械臂位置的全闭环控制奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of position estimator for rope driven Micromanipulator of surgical robot based on parameter autonomous selection model
As the micromanipulator of surgical robots works in a narrow space, it is difficult to install any position sensors at the end, so the position control and position detection cannot be accurately performed. A position estimator based on the parameter autonomous selection model is proposed to estimate the end position indirectly. Firstly, a single joint principle prototype and a position estimator model are established through the 4-Dof driving scheme of the micromanipulator and the cable-driven model. Secondly, the proposed parameter change model is combined with the parameter selection method to form a parameter autonomous selection model. Finally, a position estimator based on the parameter autonomous selection model is established. The experimental results show the maximum estimation error of the position estimator is 0.1928°. Compared with other position estimation methods, the position estimator proposed in this paper has higher accuracy and better robustness, which lays a foundation for the full closed-loop control of micromanipulator position.
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来源期刊
CiteScore
5.60
自引率
15.40%
发文量
131
审稿时长
4.5 months
期刊介绍: Fundamental theory, algorithms, design, manufacture, and experimental validation for mechanisms and robots; Theoretical and applied kinematics; Mechanism synthesis and design; Analysis and design of robot manipulators, hands and legs, soft robotics, compliant mechanisms, origami and folded robots, printed robots, and haptic devices; Novel fabrication; Actuation and control techniques for mechanisms and robotics; Bio-inspired approaches to mechanism and robot design; Mechanics and design of micro- and nano-scale devices.
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