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Pose estimation of surgical instrument using sensor data fusion with optical tracker and IMU based on Kalman filter

机译:基于卡尔曼滤波器的光学跟踪器与IMU传感器数据融合融合的手术器械姿态估计

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Tracking system is essential for Image Guided Surgery(IGS). The Optical Tracking Sensor(OTS) has been widely used as tracking system for IGS due to its high accuracy and easy usage. However, OTS has a limit that tracking fails when occlusion of marker occurs. In this paper, sensor fusion with OTS and Inertial Measurement Unit(IMU) is proposed to solve this problem. The proposed algorithm improves the accuracy of tracking system by eliminating scattering error of the sensor and supplements the disadvantages of OTS and IMU through sensor fusion based on Kalman filter. Also, coordinate axis calibration method that improves the accuracy is introduced. The performed experiment verifies the effectualness of the proposed algorithm.
机译:跟踪系统对于图像引导手术(IGS)至关重要。光学跟踪传感器(OTS)的高精度和易用性已被广泛用作IGS的跟踪系统。但是,OTS有一个局限性,即在发生标记被阻塞时跟踪会失败。为了解决这个问题,本文提出了将传感器与OTS和惯性测量单元(IMU)融合的方法。该算法通过消除传感器的散射误差,提高了跟踪系统的精度,并通过基于卡尔曼滤波的传感器融合,弥补了OTS和IMU的不足。另外,介绍了提高精度的坐标轴校准方法。所进行的实验验证了所提算法的有效性。

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