Simultaneous Location and Mapping

Simultaneous localization and mapping (SLAM), also known as real-time localization and map construction, refers to the subject equipped with sensors, which simultaneously estimates its own motion and builds a model of the environment without prior information about the environment. It is a vision algorithm mainly used by mobile robots, which allows the robot to gradually build and update a geometric model as it explores an unknown environment, and based on the built part of the model, the robot can determine its position relative to the model (self-positioning). It can also be understood that the robot starts to move from an unknown position in an unknown environment. In the process of moving, it not only performs its own positioning according to the existing map and the estimation of the position but also performs incremental map drawing on the basis of its own positioning. So as to realize the autonomous positioning and navigation of the robot [1].