Long Chen;Yuchen Li;Luxi Li;Shuangying Qi;Jian Zhou;Youchen Tang;Jianjian Yang;Jingmin Xin
{"title":"重型自动采矿车的高精度定位、感知和安全导航","authors":"Long Chen;Yuchen Li;Luxi Li;Shuangying Qi;Jian Zhou;Youchen Tang;Jianjian Yang;Jingmin Xin","doi":"10.1109/TIV.2024.3375273","DOIUrl":null,"url":null,"abstract":"Autonomous driving technology has achieved significant breakthroughs in open scenarios, enabling the deployment of excellent positioning, detection, and navigation algorithms on passenger vehicles. However, there has been limited research attention devoted to autonomous driving for specialized vehicles in non-open scenarios. This manuscript introduces a perception system designed for heavy-duty mining transportation trucks operating in open-pit mines, which are typical of non-open scenarios. The system comprises four independent algorithms: high-precision fusion positioning, multi-task 2D detection, 9 Degrees of Freedom (9 DoF) 3D head, and autonomous navigation technology. Experimental verification demonstrates the effectiveness of these methods in addressing the challenges posed by mining environments, ultimately leading to enhanced safety and efficiency for trucks. This research outcome, through the comprehensive examination of positioning, detection, and navigation, aims to address the challenges encountered by mining trucks during operations. Its significance lies in enhancing automation levels in mining scenarios.","PeriodicalId":36532,"journal":{"name":"IEEE Transactions on Intelligent Vehicles","volume":"9 4","pages":"4644-4656"},"PeriodicalIF":14.0000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-Precision Positioning, Perception and Safe Navigation for Automated Heavy-Duty Mining Trucks\",\"authors\":\"Long Chen;Yuchen Li;Luxi Li;Shuangying Qi;Jian Zhou;Youchen Tang;Jianjian Yang;Jingmin Xin\",\"doi\":\"10.1109/TIV.2024.3375273\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Autonomous driving technology has achieved significant breakthroughs in open scenarios, enabling the deployment of excellent positioning, detection, and navigation algorithms on passenger vehicles. However, there has been limited research attention devoted to autonomous driving for specialized vehicles in non-open scenarios. This manuscript introduces a perception system designed for heavy-duty mining transportation trucks operating in open-pit mines, which are typical of non-open scenarios. The system comprises four independent algorithms: high-precision fusion positioning, multi-task 2D detection, 9 Degrees of Freedom (9 DoF) 3D head, and autonomous navigation technology. Experimental verification demonstrates the effectiveness of these methods in addressing the challenges posed by mining environments, ultimately leading to enhanced safety and efficiency for trucks. This research outcome, through the comprehensive examination of positioning, detection, and navigation, aims to address the challenges encountered by mining trucks during operations. Its significance lies in enhancing automation levels in mining scenarios.\",\"PeriodicalId\":36532,\"journal\":{\"name\":\"IEEE Transactions on Intelligent Vehicles\",\"volume\":\"9 4\",\"pages\":\"4644-4656\"},\"PeriodicalIF\":14.0000,\"publicationDate\":\"2024-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Intelligent Vehicles\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10465630/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Intelligent Vehicles","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10465630/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
High-Precision Positioning, Perception and Safe Navigation for Automated Heavy-Duty Mining Trucks
Autonomous driving technology has achieved significant breakthroughs in open scenarios, enabling the deployment of excellent positioning, detection, and navigation algorithms on passenger vehicles. However, there has been limited research attention devoted to autonomous driving for specialized vehicles in non-open scenarios. This manuscript introduces a perception system designed for heavy-duty mining transportation trucks operating in open-pit mines, which are typical of non-open scenarios. The system comprises four independent algorithms: high-precision fusion positioning, multi-task 2D detection, 9 Degrees of Freedom (9 DoF) 3D head, and autonomous navigation technology. Experimental verification demonstrates the effectiveness of these methods in addressing the challenges posed by mining environments, ultimately leading to enhanced safety and efficiency for trucks. This research outcome, through the comprehensive examination of positioning, detection, and navigation, aims to address the challenges encountered by mining trucks during operations. Its significance lies in enhancing automation levels in mining scenarios.
期刊介绍:
The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges.
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