The manouver ability from one place to another in order to accomplish some tasks safely is a basic requirement of mobile robotics. Current robotic’s navigation systems require a ’real world’ map data, acquired by on-board sensors, to carry out simultaneous localisation and navigation (SLAM) algorithm. There are several SLAM algorithms. In this article we used SLAM gmapping using robot operating system (ROS) and laser scanner. The gmapping slam algorithm used particle filter method to localize robot pose within the environment and generate 2D occupancy grid map. The map is in gray-scale informed the free space, wall, and unexplored space. The implementation of gmapping slam conducted with turtlebot 3 from Robotics as well as 3D simulation using gazebo.
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