摘要
微操纵执行器末端位置的精确反馈在显微自动化操作中具有重要意义,而现有研究无法克服在复杂干扰环境下执行器末端精确跟踪的问题。针对上述提到的问题,提出一种基于语义分割模型的执行器末端位置检测跟踪方法。首先构建端到端的执行器图像语义分割模型,其次利用轮廓拐点检测算法在分割出的掩模图像中跟踪执行器末端位置,为了进一步提高算法在复杂环境中的跟踪精度及鲁棒性,利用二维卡尔曼滤波算法对遮挡情况进行处理,实现了执行器末端被遮挡时的位置跟踪。实验结果表明语义分割模型对执行器分割精度达到了62.4%,并且在复杂环境中对执行器末端位置跟踪的最大平均误差为1.51 pixels,为提升微末端执行器的操纵精度提供基础。
The precise feedback of the end position of the micro-manipulation actuator is of great significance in the micro-automation operation,and the existing research cannot overcome the problem of accurate tracking of the end of the actuator in a complex interference environment.Aiming at the above mentioned problem,a method for detecting and tracking the end position of the actuator based on the semantic segmentation model is proposed.Firstly,an end-to-end semantic segmentation model of the actuator image is built.Secondly,the contour inflection point detection algorithm is used to track the end position of the actuator in the segmented mask image.In order to further improve the tracking accuracy and robustness of the algorithm in a complex environment,2 D Kalman filter algorithm is used to process the occlusion situation,and the position tracking is realized when the end of the actuator is occluded.The experiment results show that the semantic segmentation model can achieve the segmentation accuracy of 62.4%for the actuator,and the maximum average error of tracking the end position of the actuator in a complex environment is 1.51 pixels,which provides a basis for improving the manipulation accuracy of the micro end effector.
作者
樊启高
朱高文
黄文涛
贾捷
张鹏松
Fan Qigao;Zhu Gaowen;Huang Wentao;Jia Jie;Zhang Pengsong(School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2021年第9期62-70,共9页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51807079)
江苏省自然科学基金(BK20200623)
江苏省“六大人才高峰”高层次人才项目(GDZB-138)资助。
关键词
语义分割模型
轮廓拐点检测算法
卡尔曼滤波算法
semantic segmentation model
contour inflection point detection algorithm
Kalman filter algorithm
