Simultaneous Localization and Mapping in Application to Autonomous Robot

The important characteristic that could assist in autonomous navigation is the ability of a mobile robot to concurrently construct a map for an unknown environment and localize itself within the same environment. This computational problem is known as Simultaneous Localization and Mapping (SLAM). In literature, researchers have studied this approach extensively and have proposed a lot of improvement towards it. More so, we are experiencing a steady transition of this technology to industries. However, there are still setbacks limiting the full acceptance of this technology even though the research has been conducted over the last 30 years. Thus, to determine the problems facing SLAM, this paper conducted a review on various foundation and recent SLAM algorithms. This study was carried out to discuss unresolved SLAM problem with the view that could encourage researchers to produce innovative achievements by taking the SLAM issues discussed into consideration. However, a novel SLAM technique that will address these problems will be proposed.