激光雷达
同时定位和映射
稳健性(进化)
计算机科学
遥感
人工智能
计算机视觉
传感器融合
地理
机器人
移动机器人
生物化学
基因
化学
标识
DOI:10.1109/conf-spml54095.2021.00040
摘要
LiDAR-based Simultaneous Localization and Mapping (LiDAR-SLAM) uses the LiDAR sensor to localize itself by observing environmental features and incrementally build the map of the surrounding environment. In this way, the purpose of simultaneous localization and mapping in the unknown environment can be achieved. Localization and mapping with high robustness, high accuracy, and high practicability is a complex and hot issue in recent years. This paper will briefly introduce the information background, classification and development history of LiDAR-SLAM. We will also summarize the common frameworks of LiDAR-SLAM and the function of core modules in the existing LiDAR-SLAM. Additionally, the state-of-the-art multi-sensor fusion-based LiDAR-SLAM techniques are investigated, and the future development trend of LiDAR-SLAM is discussed.
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