A survey on visual SLAM in robotics

Iman Abaspur Kazerouni, Luke Fitzgerald, Gerard Dooly, Daniel Toal, A survey of state-of-the-art on visual SLAM, Expert Systems with Applications, Volume 205, 2022 DOI: 10.1016/j.eswa.2022.117734.

This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We discuss the basic definitions in the SLAM and vision system fields and provide a review of the state-of-the-art methods utilized for mobile robot\u2019s vision and SLAM. This paper covers topics from the basic SLAM methods, vision sensors, machine vision algorithms for feature extraction and matching, Deep Learning (DL) methods and datasets for Visual Odometry (VO) and Loop Closure (LC) in V-SLAM applications. Several feature extraction and matching algorithms are simulated to show a better vision of feature-based techniques.

See also:

Jun Cheng, Liyan Zhang, Qihong Chen, Xinrong Hu, Jingcao Cai, “A review of visual SLAM methods for autonomous driving vehicles,” Engineering Applications of Artificial Intelligence, Volume 114, 2022, 104992, ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2022.104992.

Tianyao Zhang, Xiaoguang Hu, Jin Xiao, Guofeng Zhang, “A survey of visual navigation: From geometry to embodied AI,” Engineering Applications of Artificial Intelligence, Volume 114, 2022, 105036, ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2022.105036.

Comments are closed.

Post Navigation