Abstract
Simultaneous localization and mapping (SLAM) is a technique applied in artificial intelligence mobile robot for a self-exploration in numerous geographical environment. SLAM becomes fundamental research area in recent days as it promising solution in solving most of problems which related to the self-exploratory oriented artificial intelligence mobile robot field. For example, the capability to explore without any prior knowledge on environment it explores and without any human interference. The unique feature in SLAM is that the process of mapping and localization is done concurrently and recursively. Since SLAM introduction, many SLAM algorithms have been proposed to apply SLAM technique in real practice. The aim of this paper is to provide an insightful review on information background, recent development, feature, implementation and recent issue in SLAM.
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