Indoor Mobile Robot Positioning using Sensor Fusion

Trong Tai Nguyen, Dang Hien Ngo, Quoc Truong Nguyen, D. Tran, Xuan-Ba Dang
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Abstract

In this research, a low-cost positioning sensor fusion system is investigated. In which, the Ultra-wide-band system combined with IMU and robot wheel odometry are employed to improve the accuracy and resolution of robot localization by using the Extended Kalman Filter. Simulation and experimental results are carried out to validate the proposed framework. The results show the effectiveness of the method with low cost, real-time, and robustness, centimeter- level positioning accuracy.
基于传感器融合的室内移动机器人定位
本文研究了一种低成本的定位传感器融合系统。其中,结合IMU和机器人车轮里程计的超宽带系统,利用扩展卡尔曼滤波提高机器人定位的精度和分辨率。仿真和实验结果验证了所提出的框架。结果表明,该方法具有成本低、实时性好、鲁棒性好、厘米级定位精度高等优点。
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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