SLAM(Simultaneous Localization and Mapping) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
This contains package openslam_gmapping and slam_gmapping which is a ROS2 wrapper for OpenSlam's Gmapping. Using slam_gmapping, you can create a 2-D occupancy grid map (like a building floorplan) from laser and pose data collected by a mobile robot.
ros2 launch slam_gmapping slam_gmapping.launch.pyThe node slam_gmapping subscribes to sensor_msgs/LaserScan on ros2 topic scan. It also expects appropriate TF to be available.
It publishes the nav_msgs/OccupancyGrid on map.
Map Meta Data and Entropy is published on map_metadata and entropy respectively.
sudo apt install ros-humble-navigation2 ros-humble-nav2-bringup
sudo apt install ros-humble-turtlebot3*ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py
ros2 launch nav2_bringup navigation_launch.py use_sim_time:=True
ros2 launch slam_gmapping slam_gmapping.launch.py
ros2 run rviz2 rviz2 -d ~/slam_gmapping/gmapping.rviz
you can use explore lite ore teleop
ros2 run turtlebot3_teleop teleop_keyboard
