Navigation of mobile robot in 3d map

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Hi @feignedjesse2, sounds like you're doing something similar to me, so I'll try help you out as best I can. Your problem is pretty general so I can't give you specific advice without knowing more about your project and what you're trying to achieve. As always, I'll assume that you or anyone else reading this is just starting out with ROS. Let's break down what you want to do into three parts (all of the below have ROS integration):

SLAM

You want to map your environment and you need a 3D map, you're often wanting to localize your laser scanner or robot at the same time - i.e. Simultaneous Localization and Mapping (SLAM) Below are some ROS-compatible options.

• Gmapping is the most-integrated SLAM algorithm you can use with ROS, so it works well with the ROS navigation stack (below). It's essentially a ROS wrapper for the Gmapping algorithm you can find on OpenSLAM. Only does 2D SLAM but is a probably the best starting point for anyone new to ROS.
• Google Cartographer Google very recently released this 2D/3D SLAM package that will take laser and/or point cloud data and give you an occupancy map. You can find ROS integration here and Github code here. Not sure how they represent the map internally. Cartographer includes loop-closure.
• Berkley Localization and Mapping (BLAM) is another 3D LiDAR SLAM package. This doesn't have any papers on it that I am aware of, and it isn't being maintained (last commit was over two years ago). This uses the open-source and ROS-compatible Point Cloud Library for some of it's processing. Also does loop-closure
• Laser Odometry and Mapping (LOAM) is another 3D LiDAR SLAM package written by a PhD student. The source code is old and outdated because the student went on to commercialize their code with the company Kaarta. You can find a (somewhat) working version of the LOAM source code here. Does not perform any loop closure, so it's long-term use is quite limited.
• hector_slam/hector_mapping gives you LiDAR-based SLAM for systems with poor/no odometry (may suit you since you don't have wheel encoders). Also outputs an occupancy map. From memory I think this uses an elevation map (someone correct me If I'm wrong)

Of these options, I've played with Cartographer, BLAM, LOAM and Gmapping. If you're starting out with ROS and you only need 2D SLAM, I'd recommend Gmapping. If you are experienced with ROS and/or SLAM concepts, I think the 2D version of Cartographer is more accurate and robust than Gmapping. If you need a 3D solution, Cartographer is quite hard to setup, tune and use, but it is still maintained and probably a better solution long-term than BLAM. Can't recommend the LOAM code.

Mapping only

There are some packages that don't do SLAM and are only used for pure mapping (i.e. you'll have to use something else ... (more)