Abstract

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.

Keywords:
Lidar Simultaneous localization and mapping Robustness (evolution) Computer science Remote sensing Artificial intelligence Computer vision Sensor fusion Geography Robot Mobile robot

Metrics

105
Cited By
22.43
FWCI (Field Weighted Citation Impact)
49
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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