Abstract
AbstractIn this paper, we propose a comparison of open-source LiDAR and Inertial Measurement Unit (IMU)-based Simultaneous Localization and Mapping (SLAM) approaches for 3D robotic mapping. The analyzed algorithms are often exploited in mobile robotics for autonomous navigation but have not been evaluated in terms of 3D reconstruction yet. Experimental tests are carried out using two different autonomous mobile platforms in three test cases, comprising both indoor and outdoor scenarios. The 3D models obtained with the different SLAM algorithms are then compared in terms of density, accuracy, and noise of the point clouds to analyze the performance of the evaluated approaches. The experimental results indicate the SLAM methods that are more suitable for 3D mapping in terms of the quality of the reconstruction and highlight the feasibility of mobile robotics in the field of autonomous mapping.
Publisher
Cambridge University Press (CUP)
Subject
Computer Science Applications,General Mathematics,Software,Control and Systems Engineering,Control and Optimization,Mechanical Engineering,Modeling and Simulation,Artificial Intelligence,Computer Vision and Pattern Recognition,Computational Mechanics,Rehabilitation
Reference37 articles.
1. A Tutorial on Graph-Based SLAM
2. [18] Hahnel, D. , Burgard, W. , Fox, D. and Thrun, S. , “An Efficient FastSLAM Algorithm for Generating Maps of Large-Scale Cyclic Environments from Raw Laser Range Measurements,” In: Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), vol. 1 (2003) pp. 206–211.
3. Performance Investigation and Repeatability Assessment of a Mobile Robotic System for 3D Mapping
4. Building Information Modeling (BIM) for existing buildings — Literature review and future needs
Cited by
10 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献