Antonio Savio Silva Oliveira , Marcello Carvalho dos Reis , Francisco Alan Xavier da Mota , Maria Elisa Marciano Martinez , Auzuir Ripardo Alexandria
{"title":"计算机视觉在移动机器人定位中的应用新趋势","authors":"Antonio Savio Silva Oliveira , Marcello Carvalho dos Reis , Francisco Alan Xavier da Mota , Maria Elisa Marciano Martinez , Auzuir Ripardo Alexandria","doi":"10.1016/j.iotcps.2022.05.002","DOIUrl":null,"url":null,"abstract":"<div><p>This work presents a systematic review of computer vision techniques for locating mobile robots. Its main objectives are to analyze the latest technology in use to locate mobile robots. In addition, this work violated the advances achieved so far, assesses the challenges to be overcome and provides an analysis of future prospects. There is a lot of research related to the location of mobile robots, but the number of review articles on the topic is small, which makes this work of remarkable value. The research covered the works published in Web of Science, Scopus, Science Direct and IEEEXplore until June 2021. Each work found proposes a vision-based localization technique. After being analyzed individually, it can be concluded that it is necessary to assess the level of accuracy of these techniques through a single standard, it is necessary to assess the cost-benefit of the computational cost and the need for more powerful computers or systems to perform the localization task. Finally, the main contributions of this work are the creation of a table summarizing the main methods of localization by computer vision, the statistical analysis performed on the keywords of the selected works and providing an overview of this line of research that can be a basis for future research.</p></div>","PeriodicalId":100724,"journal":{"name":"Internet of Things and Cyber-Physical Systems","volume":"2 ","pages":"Pages 63-69"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667345222000128/pdfft?md5=7236985683bc963d415bdb07065f66f8&pid=1-s2.0-S2667345222000128-main.pdf","citationCount":"3","resultStr":"{\"title\":\"New trends on computer vision applied to mobile robot localization\",\"authors\":\"Antonio Savio Silva Oliveira , Marcello Carvalho dos Reis , Francisco Alan Xavier da Mota , Maria Elisa Marciano Martinez , Auzuir Ripardo Alexandria\",\"doi\":\"10.1016/j.iotcps.2022.05.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This work presents a systematic review of computer vision techniques for locating mobile robots. Its main objectives are to analyze the latest technology in use to locate mobile robots. In addition, this work violated the advances achieved so far, assesses the challenges to be overcome and provides an analysis of future prospects. There is a lot of research related to the location of mobile robots, but the number of review articles on the topic is small, which makes this work of remarkable value. The research covered the works published in Web of Science, Scopus, Science Direct and IEEEXplore until June 2021. Each work found proposes a vision-based localization technique. After being analyzed individually, it can be concluded that it is necessary to assess the level of accuracy of these techniques through a single standard, it is necessary to assess the cost-benefit of the computational cost and the need for more powerful computers or systems to perform the localization task. Finally, the main contributions of this work are the creation of a table summarizing the main methods of localization by computer vision, the statistical analysis performed on the keywords of the selected works and providing an overview of this line of research that can be a basis for future research.</p></div>\",\"PeriodicalId\":100724,\"journal\":{\"name\":\"Internet of Things and Cyber-Physical Systems\",\"volume\":\"2 \",\"pages\":\"Pages 63-69\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2667345222000128/pdfft?md5=7236985683bc963d415bdb07065f66f8&pid=1-s2.0-S2667345222000128-main.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet of Things and Cyber-Physical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667345222000128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things and Cyber-Physical Systems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667345222000128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
这项工作提出了定位移动机器人的计算机视觉技术的系统综述。它的主要目标是分析用于定位移动机器人的最新技术。此外,这项工作违反了迄今取得的进展,评估了有待克服的挑战,并分析了未来的前景。与移动机器人定位相关的研究有很多,但关于该主题的综述文章数量很少,这使得这项工作具有显著的价值。该研究涵盖了截至2021年6月在Web of Science、Scopus、Science Direct和ieee explore上发表的作品。发现的每一项工作都提出了一种基于视觉的定位技术。在单独分析之后,可以得出结论,有必要通过单一标准评估这些技术的准确性水平,有必要评估计算成本的成本效益以及对更强大的计算机或系统的需求来执行定位任务。最后,本工作的主要贡献是创建了一个表格,总结了计算机视觉定位的主要方法,对所选作品的关键词进行了统计分析,并对这一研究方向进行了概述,为今后的研究奠定了基础。
New trends on computer vision applied to mobile robot localization
This work presents a systematic review of computer vision techniques for locating mobile robots. Its main objectives are to analyze the latest technology in use to locate mobile robots. In addition, this work violated the advances achieved so far, assesses the challenges to be overcome and provides an analysis of future prospects. There is a lot of research related to the location of mobile robots, but the number of review articles on the topic is small, which makes this work of remarkable value. The research covered the works published in Web of Science, Scopus, Science Direct and IEEEXplore until June 2021. Each work found proposes a vision-based localization technique. After being analyzed individually, it can be concluded that it is necessary to assess the level of accuracy of these techniques through a single standard, it is necessary to assess the cost-benefit of the computational cost and the need for more powerful computers or systems to perform the localization task. Finally, the main contributions of this work are the creation of a table summarizing the main methods of localization by computer vision, the statistical analysis performed on the keywords of the selected works and providing an overview of this line of research that can be a basis for future research.