A Review of Common Techniques for Visual Simultaneous Localization and Mapping

Abstract

Mobile robots are widely used in medicine, agriculture, home furnishing, and industry. Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is extremely necessary and meaningful for making researches on SLAM technology. SLAM technology involves robot mechanism kinematics, logic, mathematics, perceptual detection, and other fields. However, it faces the problem of classifying the technical content, which leads to diverse technical frameworks of SLAM. Among all sorts of SLAM, visual SLAM (V-SLAM) has become the key academic research due to its advantages of low price, easy installation, and simple algorithm model. Firstly, we illustrate the superiority of V-SLAM by comparing it with other localization techniques. Secondly, we sort out some open-source V-SLAM algorithms and compare their real-time performance, robustness, and innovation. Then, we analyze the frameworks, mathematical models, and related basic theoretical knowledge of V-SLAM. Meanwhile, we review the related works from four aspects: visual odometry, back-end optimization, loop closure detection, and mapping. Finally, we prospect the future development trend and make a foundation for researchers to expand works in the future. All in all, this paper classifies each module of V-SLAM in detail and provides better readability to readers. This is undoubtedly the most comprehensive review of V-SLAM recently.