Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems
Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems
复制标题
DOI：
10.1371/journal.pone.0210385
复制
发表时间：
2019-01-11
期刊：
影响因子：
3.7
通讯作者：
Wiersma, Rodney D.
中科院分区：
文献类型：
--
作者：
Liu, Xinmin;Wiersma, Rodney D.
治疗放射束相对于动态移动的肿瘤靶的机器人稳定可以通过移动放射源、患者或两者来实现。由于治疗光束在此过程中开启，因此主要目标是在将目标移回所需位置时尽可能减少正常组织暴露于辐射。由于6自由度（6DoF）机器人的复杂机械结构，关于在实现这样的目标时什么6维（6D）校正轨迹是最佳的并不直观。利用比例-积分-微分（PID）和其他控制，控制器可能产生高度弯曲、缓慢或次优的轨迹，因为它导致健康组织不必要地暴露于辐射。这项工作研究了一种新的反馈规划方法，考虑到机器人的机械关节结构，病人的安全公差，和其他系统的约束，并进行实时优化，以搜索整个6D轨迹空间在每个时间周期，所以它可以响应最佳的6D校正轨迹。MethodsComputer模拟创建两个6DoF机器人病人支持系统：用于在无框架无掩模立体定向放射外科手术中移动患者头部的Stewart-Gough平台，以及用于在前列腺癌放射治疗中移动患者的线性加速器治疗台。运动规划被制定为一个优化问题，并使用L-BFGS算法以实时速度求解。研究了三种规划方法：尽可能快地移动平台（平台-D）、沿沿着直线移动目标（目标-S）和基于位置误差最快下降的目标（目标-D）。合成运动和事先记录的人体运动被用作输入数据和输出结果进行了analysed.ResultsFor随机生成的6D阶梯状和正弦合成输入运动，目标-D规划表现出最小的净轨迹误差在所有情况下。平均而言，最佳规划被发现有一个小45%的目标轨迹误差比平台D控制，和一个小44%的目标轨迹误差比目标S规划。对于患者头部运动补偿，只有目标-D规划能够保持
PurposeRobotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the primary goal is to minimize exposure of normal tissue to radiation as much as possible when moving the target back to the desired position. Due to the complex mechanical structure of 6 degree-of-freedom (6DoF) robots, it is not intuitive as to what 6 dimensional (6D) correction trajectory is optimal in achieving such a goal. With proportional-integrative-derivative (PID) and other controls, the potential exists that the controller may generate a trajectory that is highly curved, slow, or suboptimal in that it leads to unnecessary exposure of healthy tissue to radiation. This work investigates a novel feedback planning method that takes into account a robot's mechanical joint structure, patient safety tolerances, and other system constraints, and performs real-time optimization to search the entire 6D trajectory space in each time cycle so it can respond with an optimal 6D correction trajectory.MethodsComputer simulations were created for two 6DoF robotic patient support systems: a Stewart-Gough platform for moving a patient's head in frameless maskless stereotactic radiosurgery, and a linear accelerator treatment table for moving a patient in prostate cancer radiation therapy. Motion planning was formulated as an optimization problem and solved at real-time speeds using the L-BFGS algorithm. Three planning methods were investigated, moving the platform as fast as possible (platform-D), moving the target along a straight-line (target-S), and moving the target based on the fastest descent of position error (target-D). Both synthetic motion and prior recorded human motion were used as input data and output results were analyzed.ResultsFor randomly generated 6D step-like and sinusoidal synthetic input motion, target-D planning demonstrated the smallest net trajectory error in all cases. On average, optimal planning was found to have a 45% smaller target trajectory error than platform-D control, and a 44% smaller target trajectory error than target-S planning. For patient head motion compensation, only target-D planning was able to maintain a