Author:
Yue Xiangdi,Zhang Yihuan,Chen Jiawei,Chen Junxin,Zhou Xuanyi,He Miaolei
Abstract
Purpose
In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.
Design/methodology/approach
This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.
Findings
This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.
Originality/value
To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Control and Systems Engineering
Reference67 articles.
1. Self-driving cars: a survey;Expert Systems with Applications,2021
2. Faster-LIO: lightweight tightly coupled lidar-inertial odometry using parallel sparse incremental voxels;IEEE Robotics and Automation Letters,2022
3. Efficient surfel-based SLAM using 3D laser range data in urban environments,2018
4. The normal distributions transform: a new approach to laser scan matching,2003
5. Simultaneous localization and mapping: a survey of current trends in autonomous driving;IEEE Transactions on Intelligent Vehicles,2017
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