stands for Digital Object Identifier
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
徐仕旻 , Masters Advisor：譚俊豪
英文 DOI： 10.6844/NCKU201900550
機器人作業系統 ； 自駕車 ； 即時定位與地圖 ； 自主探索 ； 導航 ； 模型預測控制器 ； 特徵 點提取 ； 地圖合併 ； Rao-Blackwellized 粒子濾波器 ； 多車 ； ROS ； autonomous ground vehicle ； SLAM ； explore ； navigation ； Model Predict Control ； feature extraction ； map merging ； Rao-Blackwellized Particle filter ； Multi-vehicle
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-  G. Grisetti, C. Stachniss, and W. Burgard, "Improved techniques for grid mapping with rao-blackwellized particle filters," IEEE transactions on Robotics, vol. 23, no. 1, p. 34, 2007.
-  W. Hess, D. Kohler, H. Rapp, and D. Andor, "Real-time loop closure in 2D LIDAR SLAM," in 2016 IEEE International Conference on Robotics and Automation (ICRA), 2016: IEEE, pp. 1271-1278.
-  K. Konolige, G. Grisetti, R. Kümmerle, W. Burgard, B. Limketkai, and R. Vincent, "Efficient sparse pose adjustment for 2D mapping," in 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010: IEEE, pp. 22-29.
-  T. Qin, P. Li, and S. Shen, "Vins-mono: A robust and versatile monocular visual-inertial state estimator," IEEE Transactions on Robotics, vol. 34, no. 4, pp. 1004-1020, 2018.
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