Visual Simultaneous Localisation and Mapping Methodologies

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-07-25 DOI:10.2478/ama-2024-0049
Zoulikha Bouhamatou, Foudil Abdessemed
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Abstract

Simultaneous localisation and mapping (SLAM) is a process by which robots build maps of their environment and simultaneously determine their location and orientation in the environment. In recent years, SLAM research has advanced quickly. Researchers are currently working on developing reliable and accurate visual SLAM algorithms dealing with dynamic environments. The steps involved in developing a SLAM system are described in this article. We explore the most-recent methods used in SLAM systems, including probabilistic methods, visual methods, and deep learning (DL) methods. We also discuss the fundamental techniques utilised in SLAM fields.
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视觉同步定位和绘图方法
同步定位和绘图(SLAM)是机器人建立环境地图并同时确定其在环境中的位置和方向的过程。近年来,SLAM 研究进展迅速。目前,研究人员正致力于开发可靠、精确的视觉 SLAM 算法,以应对动态环境。本文介绍了开发 SLAM 系统的步骤。我们探讨了 SLAM 系统中使用的最新方法,包括概率方法、视觉方法和深度学习 (DL) 方法。我们还讨论了 SLAM 领域使用的基本技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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