大型重型汽车工业越野多传感器融合系统研究进展

De Jong Yeong, John Barry, Joseph Walsh
{"title":"大型重型汽车工业越野多传感器融合系统研究进展","authors":"De Jong Yeong, John Barry, Joseph Walsh","doi":"10.1109/ISSC49989.2020.9180186","DOIUrl":null,"url":null,"abstract":"Industry 4.0 or fourth industrial revolution elevates the computerization of Industry 3.0 and enhances it with smart and autonomous systems driven by data and Machine Learning. This paper reviews the advantages and disadvantages of sensors and the architecture of multi-sensor setup for object detection. Here we consider the case of autonomous systems in for large heavy vehicles off-road in industrial environments with the use of camera sensor, LiDAR sensor, and radar sensor. Understanding the vehicles surroundings is a vital task in autonomous operation where personnel and other obstacles present significant hazard of collision. This paper review further discusses the challenges of time synchronisation on sensor data acquisition in multi-modal sensor fusion for personnel and object detection, and details a solution implemented in a Python environment.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A Review of Multi-Sensor Fusion System for Large Heavy Vehicles Off Road in Industrial Environments\",\"authors\":\"De Jong Yeong, John Barry, Joseph Walsh\",\"doi\":\"10.1109/ISSC49989.2020.9180186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industry 4.0 or fourth industrial revolution elevates the computerization of Industry 3.0 and enhances it with smart and autonomous systems driven by data and Machine Learning. This paper reviews the advantages and disadvantages of sensors and the architecture of multi-sensor setup for object detection. Here we consider the case of autonomous systems in for large heavy vehicles off-road in industrial environments with the use of camera sensor, LiDAR sensor, and radar sensor. Understanding the vehicles surroundings is a vital task in autonomous operation where personnel and other obstacles present significant hazard of collision. This paper review further discusses the challenges of time synchronisation on sensor data acquisition in multi-modal sensor fusion for personnel and object detection, and details a solution implemented in a Python environment.\",\"PeriodicalId\":351013,\"journal\":{\"name\":\"2020 31st Irish Signals and Systems Conference (ISSC)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 31st Irish Signals and Systems Conference (ISSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSC49989.2020.9180186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 31st Irish Signals and Systems Conference (ISSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSC49989.2020.9180186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

工业4.0或第四次工业革命提升了工业3.0的计算机化,并通过数据和机器学习驱动的智能和自主系统增强了它。本文综述了传感器的优点和缺点,以及用于目标检测的多传感器装置的结构。在这里,我们考虑在工业环境中使用相机传感器、激光雷达传感器和雷达传感器的大型重型车辆越野自动驾驶系统的情况。在人员和其他障碍物存在重大碰撞危险的自动驾驶中,了解车辆周围环境是一项至关重要的任务。本文进一步讨论了在人员和目标检测的多模态传感器融合中传感器数据采集的时间同步挑战,并详细介绍了在Python环境中实现的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Review of Multi-Sensor Fusion System for Large Heavy Vehicles Off Road in Industrial Environments
Industry 4.0 or fourth industrial revolution elevates the computerization of Industry 3.0 and enhances it with smart and autonomous systems driven by data and Machine Learning. This paper reviews the advantages and disadvantages of sensors and the architecture of multi-sensor setup for object detection. Here we consider the case of autonomous systems in for large heavy vehicles off-road in industrial environments with the use of camera sensor, LiDAR sensor, and radar sensor. Understanding the vehicles surroundings is a vital task in autonomous operation where personnel and other obstacles present significant hazard of collision. This paper review further discusses the challenges of time synchronisation on sensor data acquisition in multi-modal sensor fusion for personnel and object detection, and details a solution implemented in a Python environment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Effects of Intra-Subject Variation in Gait Analysis on ASD Classification Performance in Machine Learning Models Practical Implementation of APTs on PTP Time Synchronisation Networks Not Everything You Read Is True! Fake News Detection using Machine learning Algorithms Semi-Supervised Learning with Generative Adversarial Networks for Pathological Speech Classification Reduced Complexity Approach for Uplink Rate Trajectory Prediction in Mobile Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1