Tracking technology based on permanent magnetic provide a wireless,high-precision,low-cost solution for the fields of motion tracking,robot positioning and navigation,and medical device tracking.Aiming at the problems that the tracking approach based on the magnetic dipole model and Levenberg-Marquardt(LM)algorithm depends too much on initial values and limited computing time,the penalty function is constructed using constraint condition of priori knowledge based on magnetic dipole model,a permanent magnetic tracking approach fuses DenseNet and SE Block is proposed.The experimental result shows that the tracking precision is(1.79±1.05)mm and 1.12°±0.53° in height range of 48～118 mm,and the average computing time is reduced to 1.6 ms.This approach improves the computing speed and computational stability of the permanent magnetic tracking system.
关键词
磁定位/深度学习/密集卷积网络/注意力机制
Key words
magnetic tracking/deep learning/dense convolutional network(DenseNet)/attention mechanism
维普
万方数据