Eliminating UWB Self Positioning Error Based on Kalman Filter Algorithm

Yan-hua Zeng, Shaodong Shen
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Abstract

With the deep integration of the medical industry [1] and big data, Ultra-Wideband(UWB) technology has also developed rapidly in the medical industry, and a variety of medical robots have been born. The auxiliary positioning in the medical robot is the top priority. The robot auxiliary positioning system always has the problem that its own error is large, resulting in inaccurate positioning. Therefore, this paper improves the Ultra-Wideband positioning system of the medical robot based on two-dimensional trilateral positioning, and uses the Kalman filter algorithm to solve the error and positioning point drift caused by the robot itself, It can better assist positioning.
基于卡尔曼滤波算法的超宽带自定位误差消除
随着医疗行业[1]与大数据的深度融合,超宽带(UWB)技术在医疗行业也得到了快速发展,各种医疗机器人应运而生。医疗机器人的辅助定位是重中之重。机器人辅助定位系统一直存在自身误差大,导致定位不准确的问题。因此,本文对基于二维三边定位的医疗机器人超宽带定位系统进行了改进,并采用卡尔曼滤波算法解决了机器人自身造成的误差和定位点漂移问题,能够更好地辅助定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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