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A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

Debeunne, César and Vivet, Damien A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping. (2021) Sensors, 20 (7). 2068. ISSN 1424-8220

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Official URL: https://doi.org/10.3390/s20072068

Abstract

Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities.

Item Type:Article
Additional Information:This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control
HAL Id:hal-03194035
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
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Funders:
ANR-17-CE22-0001-01 - FUI STAR: DOS0075476 00
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Deposited On:09 Apr 2021 09:47

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