We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping.
- Authors
Debeunne, César; Vivet, Damien
- 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.
- Subjects
SLAM (Robotics); AUTONOMOUS underwater vehicles; DRIVERLESS cars; NAVIGATION
- Publication
Sensors (14248220), 2020, Vol 20, Issue 7, p2068
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s20072068