摘要
为了对放疗床进行结构标定,以提高放疗床的定位精度,提出了一种遗传算法与最小最大优化方法相结合的参数辨识方法。根据机构的运动学逆解建立了放疗床的标定模型;结合遗传算法与最小最大优化方法的优点对放疗床的60个参数进行参数辨识,有效减小了目标函数的残差;以激光跟踪仪作为测量工具,对若干组任意位姿进行绝对定位精度实验和重复定位位置精度实验,以验证参数辨识结果。实验结果表明,经过标定后放疗床的绝对定位精度的位置误差小于0.3mm,姿态误差小于0.1°;重复定位位置精度的位置误差小于0.01mm。故所提出的参数辨识方法能够实现对放疗床的标定,且标定精度能够满足放疗床的使用要求。
In order to conduct structural calibrations of the radiotherapy beds,and to improve their positioning accuracy,a new parameter identification method was proposed,which combined the genetic algorithm with mini-max optimization.Firstly,the calibration model of the radiotherapy bed was established based on the inverse kinematics.Then,the genetic algorithm and mini-max optimization methods,whose advantages were combined to identify 60 parameters,the residuals of the target function were reduced effectively.Finally,the laser tracker was taken to conduct two precision experiments,i.e.absolute positioning accuracy and repeated positioning accuracy experiments,for several groups of arbitrary poses,which were used to verify the results of parameter identification.The experimental results show that,for the positioning accuracy of calibrated radiotherapy beds,for the absolute positioning accuracy the position errors are less than 0.3 mm,and the attitude errors are less than 0.1°;for the repeated positioning accuracy,the position errors are less than 0.01 mm.Therefore,the parameter identification method may realize the calibrations of the radiotherapy beds,and the accuracy may meet the requirements.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2018年第1期57-62,共6页
China Mechanical Engineering
基金
国家高技术研究发展计划(863计划)资助项目(2015AA043200)
关键词
放疗床
定位精度
运动学标定
参数辨识
遗传算法
radiotherapy bed
positioning accuracy
kinematics calibration
parameter identification
genetic algorithm
