油气站智能巡检机器人定位导航系统设计

Proceedings of the 2022 9th International Conference on Wireless Communication and Sensor Networks Pub Date : 2022-01-11 DOI:10.1145/3514105.3514122

Tianxing Zhou, Tianxin Li, Chunyu Wen, Haoming Shi

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引用次数: 0

摘要

为解决油气站巡检难、产品事故频发的问题，本项目设计了一种基于传感器融合算法的油气站智能巡检车。本课题采用卡尔曼滤波算法对GNSS和IMU采集的数据进行融合。通过仿真实验得出，该算法可在低成本条件下获得高精度定位数据，可有效应用于工业生产，有利于自动驾驶巡检车的推广。

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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Design of A Positioning and Navigation System for Intelligent Inspection Robots in Oil and Gas Stations

In order to solve the problem of difficult inspections in oil and gas stations and prone to product accidents, this project designed an intelligent inspection vehicle for oil and gas stations based on sensor fusion algorithms. This project uses the Kalman filter algorithm to fuse the data collected by GNSS and IMU. Through simulation experiments, it is concluded that the algorithm can obtain high-precision positioning data under low-cost conditions, which can be effectively used in industrial production and is conducive to the promotion of self-driving inspection vehicles.

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Proceedings of the 2022 9th International Conference on Wireless Communication and Sensor Networks

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