Abstract

Simultaneous localization and mapping (SLAM), also known as concurrent mapping and localization (CML), is an important topic or robotics files. This method produces a real-time map of an environment and finds the current position of a robot on that map. This method is generally used to solve the problem of “Where am I?” for localization, “Where do I go?” for goal determination, and “How do I go there?” for robot motion planning. Recently, the number of studies in this area has increased rapidly and expanded to different areas. In this paper analyzes SLAM or CML, which is currently a hot topic in the field of robotic research. In addition, this paper describes methods for solving SLAM problems, presents evaluation methods for SLAM, analyzes recent research on SLAM worldwide, and studies the academic importance of SLAM. This paper also reviews the use of SLAM for humanoid robots and aims to address the issue of the significance of SLAM engine in the future of stereo vision on humanoid robots.

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