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EN
Simultaneous localisation and mapping (SLAM) is a process by which robots build maps of their environment and simultaneous-ly determine their location and orientation in the environment. In recent years, SLAM research has advanced quickly. Researchers are cur-rently working on developing
reliable and accurate visual SLAM algorithms dealing with dynamic environments. The steps involved in de-veloping a SLAM system are described in this article. We explore the most-recent methods used in SLAM systems, including probabilistic methods, visual methods, and deep learning (DL) methods. We also discuss the fundamental techniques utilised in SLAM fields.
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