Comments (2)
Hi,
It handles dynamic objects implicitly when a new node is added in the map, but only for 2D mapping (2D maps). For example, the new laser scan will write over obstacle cells to clean objects removed. If the robot is not moving, the map is not updated though, so the removed object would be still there. For the 3D point cloud, there is no filtering (only temporary if you set <param name="cloud_frustum_culling" type="bool" value="true"
for the rtabmap/cloud_map
output topic).
rtabmapviz and MapCloud plugin don't do frustum culling. They only keep the latest node in a fixed radius. In rtabmapviz, you can change this setting under 3D rendering panel in Preferences. For MapCloud plugin in RVIZ, there are Node filtering radius
and Node filtering angle
parameters. For all map output topics from rtabmap node: see map_filter_radius
and map_filter_radius
parameters.
The octomap can be generated from a service request to rtabmap node: /rtabmap/octomap_full
or /rtabmap/octomap_binary
services. Or you can connect /rtabmap/cloud_map
topic to an octomap_server, for which an octomap will be built again on each map update (so including graph optimization following a loop closure). You may want to tune the output /rtabmap/cloud_map
topic to generate less points. See cloud_map
related parameters of rtabmap node. Well, the map_assembler node is not required anymore to assemble a point cloud, the rtabmap node does it too as shown above.
cheers
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In that case, I will build my own octomap from sensor and location data and use raytracing to clean map from removed obstacles. Loop closure will be probably very expensive and I may have to integrate only some nodes (discard similar ones), but I believe it should be feasible. Thank you!
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Related Issues (20)
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- iOS: Add option to export in LAS format
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- Where to Integrate a body filter into custom build HOT 3
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- GUI is blank HOT 4
- Regression on RHEL for Jazzy with latest 0.21.5 version HOT 7
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