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are your LIDAR sensors 2D? 3D? Do you need the map as your robot moves through the environment (SLAM) or do you simply need a resultant map when the robot is done (reconstruction). The former is a more popular research topic and you'll find a larger number of options that may satisfy your needs. The latter takes advantage of being able to "see into the future" when registering points, and can result in a more consistent end map, especially when considering things like loop closure.

There are several ROS packages out there that will take LIDAR and IMU data to produce 3D maps, of varying fidelity. In my experience, IMU and depth information alone are enough for decent mapping, though GPS can certainly help with loop closure over larger maps. Many of them allow you to export and import generated maps to allow for reuse, if that's what you meant by "archive".. Deciding between them will depend on your requirements for computational efficiency, map resolution, map scalability, etc.

The multiple LIDAR sensor fusion might make things a bit more complicated. This question (#261259) suggests cob_scan_unifier to merge 2D LIDAR scans, for use with gmapping, but I haven't used it myself. For multiple 3D scans, presumably you'd first want to apply any transform necessary to get them all in the same frame, then concatenate the pointcloud messages from each sensor into a single combined message.

Once you have your fused LIDAR message, you could see if one of the following meets your needs:

• hdl_graph_slam
• cartographer_ros
• rtabmap_ros
• LeGO-LOAM

are your LIDAR sensors 2D? 3D? [edit - I just noticed the 3DPointCloud2 tag, so presumably 3D] Do you need the map as your robot moves through the environment (SLAM) or do you simply need a resultant map when the robot is done (reconstruction). The former is a more popular research topic and you'll find a larger number of options that may satisfy your needs. The latter takes advantage of being able to "see into the future" when registering points, and can result in a more consistent end map, especially when considering things like loop closure.

There are several ROS packages out there that will take LIDAR and IMU data to produce 3D maps, of varying fidelity. In my experience, IMU and depth information alone are enough for decent mapping, though GPS can certainly help with loop closure over larger maps. Many of them allow you to export and import generated maps to allow for reuse, if that's what you meant by "archive".. Deciding between them will depend on your requirements for computational efficiency, map resolution, map scalability, etc.

The multiple LIDAR sensor fusion might make things a bit more complicated. This question (#261259) suggests cob_scan_unifier to merge 2D LIDAR scans, for use with gmapping, but I haven't used it myself. For multiple 3D scans, presumably you'd first want to apply any transform necessary to get them all in the same frame, then concatenate the pointcloud messages from each sensor into a single combined message.

Once you have your fused LIDAR message, you could see if one of the following meets your needs:

• hdl_graph_slam
• cartographer_ros
• rtabmap_ros
• LeGO-LOAM