Visual simultaneous localization and mapping: a survey
Visual simultaneous localization and mapping: a survey
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DOI：
10.1007/s10462-012-9365-8
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发表时间：
2015-01-01
影响因子：
12
通讯作者：
Manuel Rendon-Mancha, Juan
中科院分区：
文献类型：
--
作者：
Fuentes-Pacheco, Jorge;Ruiz-Ascencio, Jose;Manuel Rendon-Mancha, Juan
视觉SLAM(同时定位和地图绘制)是指利用图像作为外部信息的唯一来源，以确定机器人、车辆或运动摄像头在环境中的位置，同时构建所探索区域的表示。SLAM对于机器人的自主性来说是一项基本任务。目前，当激光或声纳等距离传感器用于构建小静态环境的二维地图时，SLAM问题被认为得到了解决。然而，对于动态、复杂和大范围的环境，使用视觉作为唯一的外部传感器的SLAM是一个活跃的研究领域。计算机视觉技术在视觉SLAM中的应用，如显著特征的检测、描述和匹配、图像识别和检索等，仍有待改进。本文的目的是为视觉SLAM领域的新研究人员提供对最新技术的简短和可理解的回顾。
Visual SLAM (simultaneous localization and mapping) refers to the problem of using images, as the only source of external information, in order to establish the position of a robot, a vehicle, or a moving camera in an environment, and at the same time, construct a representation of the explored zone. SLAM is an essential task for the autonomy of a robot. Nowadays, the problem of SLAM is considered solved when range sensors such as lasers or sonar are used to built 2D maps of small static environments. However SLAM for dynamic, complex and large scale environments, using vision as the sole external sensor, is an active area of research. The computer vision techniques employed in visual SLAM, such as detection, description and matching of salient features, image recognition and retrieval, among others, are still susceptible of improvement. The objective of this article is to provide new researchers in the field of visual SLAM a brief and comprehensible review of the state-of-the-art.