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全局感知AGV的导航控制技术研究

KUANG Xinghong LIANG Dingqian SHI Yu KONG Jie

机械科学与技术2025,Vol.44Issue(12):2069-2077,9.
机械科学与技术2025,Vol.44Issue(12):2069-2077,9.DOI:10.13433/j.cnki.1003-8728.20230377

全局感知AGV的导航控制技术研究

Research on Navigation Control Technology of Global Aware AGV

KUANG Xinghong 1LIANG Dingqian 1SHI Yu 2KONG Jie3

作者信息

  • 1. College of Engineering Science and Technology,Shanghai Ocean University,Shanghai 201306,China
  • 2. School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
  • 3. School of Software,Jiangxi Agricultural University,Nanchang 330045,China
  • 折叠

摘要

Abstract

Aiming at the problems of insufficient positioning accuracy,high positioning cost,single field of view,and poor flexibility of conventional Automated Guided Vehicle(AGV)control in the indoor navigation process,a high-precision navigation control system for Mecanum wheel AGV with global vision is proposed in this paper.Global vision involves mounting a camera at a high location indoors and shoot to form a two-dimensional plane.Firstly,it obtains the real-time coordinate information of the AGV and its surroundings through the recognition algorithm of YOLOv5 and camera calibration.The obtained AGV positioning information is then adaptively fused with its inertial navigation positioning on the AGV using the Extended Kalman Filter algorithm to achieve more accurate positioning.And finally through the analysis of the motion kinematics of the Mecanum wheel AGV,real-time correction of the AGV's motion is achieved using fuzzy PID and decoupling control methods to achieve the navigation control objective.In the final experiment verification,the positioning control accuracy of the AGV can reach within 10 cm,resulting in a noticeable improvement in positioning navigation.

关键词

室内导航/全局感知/卡尔曼滤波/模糊PID

Key words

indoor positioning/global awareness/Kalman filtering/fuzzy PID

分类

信息技术与安全科学

引用本文复制引用

KUANG Xinghong,LIANG Dingqian,SHI Yu,KONG Jie..全局感知AGV的导航控制技术研究[J].机械科学与技术,2025,44(12):2069-2077,9.

基金项目

国家重点研发计划(2022YFC3104001) (2022YFC3104001)

机械科学与技术

OA北大核心

1003-8728

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