SLAM(Simultaneous Localization and Mapping) is the command problem in embodied AI & robotics that requires 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.
As sometimes we require building a new map based on modifyed environment and wish to abort what have been built, common approach to this would be re-start SLAM node, which is not condidarable in certain context due to its non-efficiency or other reasons.
In this project, I have altered the sourse code from SLAM_GMAPPING and added a server so that you can clear the current map built at anytime and build a new map without re-boot your SLAM node.
Clone the repo:
git clone https://github.com/HuskyKingdom/ros2_humble_gmapping.git
Put the project files under your ROS2 workspace and build the source files:
cd <your_workspace>
colcon build --packages-select ros2_humble_gmapping
Sourcing your underlay & overlay first, then launch the pipeline through the following:
cd ros2_humble_gmapping/launch
ros2 launch pipeline_launch.py
The node slam_gmapping subscribes to sensor_msgs/LaserScan on ros2 topic scan. It publishes the nav_msgs/OccupancyGrid on /maptopic.
You can customize the TF nodes in launch file if needed.
Map Meta Data and Entropy is published on map_metadata and entropy respectively.
The node starts a server /map_clear_serve which takes requests in type std_srvs/srv/Empty and response with the same tyoe. Once this server was called, the node will clear the current map and build a new one.