Department of Mechanical Engineering, University of Arkansas, Fayetteville, AR, 72701, USA.
Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, 37212, USA.
Ann Biomed Eng. 2019 Nov;47(11):2322-2333. doi: 10.1007/s10439-019-02311-3. Epub 2019 Jun 19.
This paper presents a hardware and software system to implement the task space control of an MR-conditional robot by integrating inductively coupled wireless coil based tracking feedback into the control loop. The main motivation of this work is to increase the accuracy performance and address the system uncertainties in the practical scenarios. We present the MR-conditional robot hardware design, wireless tracking method, and custom-designed communication software for real-time tracking data transfer. Based on these working principles, we fabricate the robot platform and evaluate the complete system with respect to various performance indices, i.e. data communication speed, targeting accuracy, tracking coil resolution, image quality, temperature variation, and task space control accuracy for static and dynamic targeting inside MRI scanner. The in-scanner targeting results show that the MR-conditional robot with wireless tracking coil feedback achieves the targeting error of 0.17 ± 0.08 mm, while the error calculated from the joint space optical encoder feedback is 0.68 ± 0.19 mm.
本文提出了一种硬件和软件系统,通过将基于感应耦合无线线圈的跟踪反馈集成到控制回路中,实现了磁共振(MR)条件机器人的任务空间控制。这项工作的主要动机是提高精度性能,并解决实际场景中的系统不确定性。我们介绍了 MR 条件机器人的硬件设计、无线跟踪方法和定制设计的用于实时跟踪数据传输的通信软件。基于这些工作原理,我们制造了机器人平台,并针对各种性能指标(例如数据通信速度、目标精度、跟踪线圈分辨率、图像质量、温度变化和磁共振成像(MRI)扫描仪内静态和动态目标的任务空间控制精度)对整个系统进行了评估。在扫描仪内的目标定位结果表明,具有无线跟踪线圈反馈的 MR 条件机器人实现了 0.17 ± 0.08 毫米的目标定位误差,而从关节空间光学编码器反馈计算得到的误差为 0.68 ± 0.19 毫米。