1.Simultaneous Localization and Mapping(SLAM)_Part I下载

weixin_39821260 2019-05-14 11:00:13

1.Simultaneous Localization and Mapping(SLAM)_Part I
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1.Simultaneous Localization and Mapping(SLAM)_Part I

Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods

SLAM for Dummies A Tutorial Approach to Simultaneous Localization and Mapping 由入门到放弃

slam(simultaneous localization and mapping)仿真很好的入门东西

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

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