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Map visualization
First, make sure you have an instance of roscore running. If not, you can start it in a terminal
roscore &
Then, start the maplab console:
rosrun maplab_console maplab_console
Now, load a map, and visualize it:
load --map_folder MH_01_easy # or any other VI map you have.
v
The command v
publishes the map via the ROS messages (and registers the corresponding ROS topics). Start RViz in a new terminal:
rviz
On the Displays pane on the left side, click on Add. (If you don't have the Displays pane, you can get it via Panels -> Displays)
Click on the tab By topic and select a topic to visualize and click OK on the bottom right:
Start the maplab console:
rosrun maplab_console maplab_console
Load a map, and visualize it:
load --map_folder MH_01_easy # or any other VI map you have.
v
This will publish the following topics to RViz:
-
vi_map_baseframe
: Baseframes of the individual missions of the maps. -
vi_map_edges/viwls
: Edges of the VI map. Visualization of edges: -
vi_map_vertices
: Vertex transformations. Visualzation of edges and vertices: -
vi_map_landmarks
: Point cloud of all landmarks. Visualization of edges, vertices and landmarks:
Loop closing a map (with the lc
command) adds the visualization topic loop_closures
, which will show merged landmark pairs:
Running relax
adds the topic vi_map_edges/loop_closure
to the list and displays loop closure edges between vertices that can be loop-closed:
-
vis_scale
: Sets the size of the edges. -
vis_color_by_mission
: colors the landmarks and edges of each mission differently. This is enabled by default. -
vis_color_landmarks_by_height
: Colors the landmarks by height. Use with these additional flags:vis_color_by_height_period_m
vis_color_by_height_offset_m
-
vis_color_salt
: Changes the rotation of the colors, e.g.
Salt 1 (default value):
v --vis_color_by_mission --vis_color_salt 1
Salt 70:
v --vis_color_by_mission --vis_color_salt 70
You can use
plot_vi_states_of_mission
to plot the VI states of a mission.
This will open a plot with the position, velocity, and accelerometer/gyroscope biases. This may be helpful for tuning the IMU parameters or better understanding what happens during the batch optimization.