Algorithm Research of Magnetometer Assisted Inertial Navigation System for Mobile Robots

2019 IEEE THE 2nd INTERNATIONAL CONFERENCE ON MICRO/NANO SENSORS for AI, HEALTHCARE, AND ROBOTICS (NSENS) Pub Date : 2019-10-31 DOI:10.1109/NSENS49395.2019.9293998

Yingjiao Rong, Yentze Ko, Xinan Wang, G. Shi

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Abstract

Mobile robots have broad application prospects in military, industrial, agricultural, commercial, transportation, and logistics fields. The core problem of mobile robot lies in the autonomous navigation ability of mobile robot. Inertial navigation system based on MEMS sensor is one of the research hotspots in the field of inertial navigation in recent years and one of the main research directions in the future. Aiming at the positioning of the mobile robot, this paper adopts the magnetometer assisted inertial navigation system, the navigation system consisting of a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer. The heading is calculated with three sensors, the velocity error is compensated, and calculate the position. In this paper, an Extended Kalman Filter for mobile robot navigation system is proposed to improve the position accuracy of the navigation system. Experiments are carried out to verify and analyze the filter with the experimental results.

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移动机器人磁强计辅助惯性导航系统算法研究

移动机器人在军事、工业、农业、商业、交通运输、物流等领域有着广阔的应用前景。移动机器人的核心问题在于移动机器人的自主导航能力。基于MEMS传感器的惯性导航系统是近年来惯性导航领域的研究热点之一，也是未来的主要研究方向之一。针对移动机器人的定位，本文采用了磁强计辅助惯性导航系统，该导航系统由三轴加速度计、三轴陀螺仪和三轴磁强计组成。用三个传感器计算航向，补偿速度误差，计算位置。为了提高移动机器人导航系统的定位精度，提出了一种扩展的卡尔曼滤波方法。利用实验结果对该滤波器进行了验证和分析。

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2019 IEEE THE 2nd INTERNATIONAL CONFERENCE ON MICRO/NANO SENSORS for AI, HEALTHCARE, AND ROBOTICS (NSENS)

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