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It is my understanding that gmapping is the recommended mapping engine for the Navigation stack (https://wiki.ros.org/navigation/MapBu...). Is gmapping still the best tool for creating a 2D map (given the 3D lidar)?

Personally, I'd use Slam Toolbox, but I'm also horribly biased. I see you're working with a Hokuyo, that was my main platform for development for that project so I'd expect good out of the box results. Other options are Hector, Karto, and Cartographer (though abandoned).

I want to create a 2D map, but avoid obstacles using the full 3D lidar data (exactly like the video on the navigation stack home page: https://wiki.ros.org/navigation). Using the navigation stack with gmapping, and amcl will I be able to reach this objective?

Yes. The 2D lidar will be used for localization and mapping, The "3D" sweeping lidar points can be used for collision avoidance in the costmaps.

Can you please recommend package combinations that will allow the robot to build a 2D map, localize in the map, and navigate to points on the map while avoiding obstacles using the full horizontal 3D lidar data?

The generic toolset will do this fine. The "3D" steeping lidar is essentially just a pointcloud generator which the Voxel Layer (or STVL) can handle.

Personally, I wouldn't go for the sweeping 2D lidar anymore, depth cameras are ubiquitous and cheap. But since you have it, you should use it since those are $$$. In the future though, look at the Orbbec or Realsense cameras. They're about ~$200 and mechanically simplier.

It is my understanding that gmapping is the recommended mapping engine for the Navigation stack (https://wiki.ros.org/navigation/MapBu...). Is gmapping still the best tool for creating a 2D map (given the 3D lidar)?

Personally, I'd use Slam Toolbox, but I'm also horribly biased. I see you're working with a Hokuyo, that was my main platform for development for that project so I'd expect good out of the box results. Other options are Hector, Karto, and Cartographer (though abandoned).abandoned), and LAMA.

I want to create a 2D map, but avoid obstacles using the full 3D lidar data (exactly like the video on the navigation stack home page: https://wiki.ros.org/navigation). Using the navigation stack with gmapping, and amcl will I be able to reach this objective?

Yes. The 2D lidar will be used for localization and mapping, The "3D" sweeping lidar points can be used for collision avoidance in the costmaps.

Can you please recommend package combinations that will allow the robot to build a 2D map, localize in the map, and navigate to points on the map while avoiding obstacles using the full horizontal 3D lidar data?

The generic toolset will do this fine. The "3D" steeping lidar is essentially just a pointcloud generator which the Voxel Layer (or STVL) can handle.

Personally, I wouldn't go for the sweeping 2D lidar anymore, depth cameras are ubiquitous and cheap. But since you have it, you should use it since those are $$$. In the future though, look at the Orbbec or Realsense cameras. They're about ~$200 and mechanically simplier.

It is my understanding that gmapping is the recommended mapping engine for the Navigation stack (https://wiki.ros.org/navigation/MapBu...). Is gmapping still the best tool for creating a 2D map (given the 3D lidar)?

Personally, I'd use Slam Toolbox, but I'm also horribly biased. I see you're working with a Hokuyo, that was my main platform for development for that project so I'd expect good out of the box results. Other options are Hector, Karto, and Cartographer (though abandoned), and LAMA.

I want to create a 2D map, but avoid obstacles using the full 3D lidar data (exactly like the video on the navigation stack home page: https://wiki.ros.org/navigation). Using the navigation stack with gmapping, and amcl will I be able to reach this objective?

Yes. The 2D lidar will be used for localization and mapping, The "3D" sweeping lidar points can be used for collision avoidance in the costmaps.

Can you please recommend package combinations that will allow the robot to build a 2D map, localize in the map, and navigate to points on the map while avoiding obstacles using the full horizontal 3D lidar data?

The generic toolset will do this fine. The "3D" steeping lidar is essentially just a pointcloud generator which the Voxel Layer (or STVL) can handle.

Personally, I wouldn't go for the sweeping 2D lidar anymore, depth cameras are ubiquitous and cheap. But since you have it, you should use it since those are $$$. In the future though, look at the Orbbec or Realsense cameras. They're about ~$200 and mechanically simplier.