摘要
为进行水面无人艇运动姿态数据采集与可视化监测,基于LoRa设计研发了水面无人艇远程数据采集系统。该系统能够实现卫星定位及船舶六自由度运动姿态数据的采集,通过LoRa通信模块实现数据远程发送与接收,并基于上位机对位姿数据进行可视化展示,实现水面无人艇位姿远程数据可视化监测。最终实验结果显示,系统各项功能稳定运行,数据采集及传输功能平稳,上位机所展示的可视化界面清晰直观,效果良好。该系统的数据采集、处理、传输、显示与保存等功能的实现,能够为无人艇操纵运动建模、基于运动模型的自动控制系统设计、航海仿真系统中以数据驱动目标船舶、无人艇远程岸基运动监测与指挥等提供数据支持,为水面无人艇的技术发展、科研与教学实验等提供技术支持。
In order to collect and visually monitor the motion attitude data of USV(unmanned surface vehicle),a remote data acquisition system for USV is designed and developed based on LoRa.The system can realize satellite positioning and acquisition of six degree of freedom motion attitude data of ships,achieve remote sending and receiving of data by means of LoRa communication module,and visually display the pose data on the basis of upper computer,so as to realize remote visual monitoring of pose data of USV.The experimental results show that all functions(including data acquisition and transmission functions of the system can operate stably,and the visualization interface displayed by the upper computer is clear and intuitive.The data acquisition,processing,transmission,display and storage functions of the system can provide data support for USV maneuvering motion modeling,automatic control system design based on motion model,data driving of the target ship in navigation simulation system,remote shore-based monitoring and command of USV motion,etc.,and provide technical support for technical development,scientific research and teaching experiments of USV.
作者
田延飞
周欣蔚
温小飞
王海荣
陈立家
TIAN Yanfei;ZHOU Xinwei;WEN Xiaofei;WANG Hairong;CHEN Lijia(School of Naval Architecture and Maritime,Zhejiang Ocean University,Zhoushan 316022,China;Zhoushan Institute of Calibration and Testing for Quality and Technology Supervision,Zhoushan 316000,China;Hubei Key Laboratory of Inland Shipping Technology,Wuhan 430063,China;School of Navigation,Wuhan University of Technology,Wuhan 430063,China)
出处
《现代电子技术》
2022年第22期23-27,共5页
Modern Electronics Technique
基金
浙江省教育厅一般项目(Y202147772)
2021浙江省大学生科技创新活动计划(2021R1036)
浙江省市场监督管理局质量技术基础建设项目(20200132)
国家重点研发计划项目(2018YFC0810405)
国家重点研发计划项目(2018YFC1407403)。
