Costmap doesn't consider laser beams behind the robot (only when the laser frame is flipped upside down)

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Hello everyone,

I'm currently implementing the navstack on my robot and I have a problem with the generation of my costmaps : I use the obstacle layer plugin to make dynamic obstacles from the LiDAR that is mounted under my robot. As it is upside down, I use a static tf publisher to indicate "laser" (my laser frame) is upside down compared to "base_link". When I do so, the LaserScan published on /scan topic works well and the obstacles are visibles and coherent with their position around the robot. BUT, when I use move_base, the cosmaps (both global and local leverage from an obstacle layer) don't consider the laser beams behind the robot as obstacles(no obstacle points and no inflation neither). see rviz screenshot here : https://drive.google.com/file/d/1cOVd...

When searching for a solution I realized that another robot of mine (with a LiDAR facing up) with the exact same move_base configuration works well (every laser beam is taken as an obstacle). I tested changing the orientation of the laser frameby putting no reversal in the static tf publisher and this time, all points are considered correctly (but obviously every point position is reversed). see attached screenshot : https://drive.google.com/file/d/1o41B...

If anyone has any idea or suggestion about how to debugg this, i'd be glad to hear it.

Here is my static tf publisher

<launch>
<node pkg="tf" type="static_transform_publisher" name="laser_tf_pub" args="0 0 0 -0.785 3.14 0 base_link laser 100" />
</launch>

yaw rotation of -0.785 rad is also needed. Here are my local and global costmaps yaml files :

local_costmap:
  global_frame: odom
  robot_base_frame: base_footprint

  update_frequency: 10.0
  publish_frequency: 10.0
  transform_tolerance: 0.5  

  footprint: [[-0.765, -0.455], [-0.765, 0.455], [0.765, 0.455], [0.765, -0.455]]
  footprint_padding: 0.03
  robot_radius: 0.15
  static_map: true  
  rolling_window: true
  width: 3
  height: 3
  resolution: 0.05
  plugins:
    - {name: static_map, type: "costmap_2d::StaticLayer"}
    - {name: obstacles, type: "costmap_2d::ObstacleLayer"}
    - {name: inflation, type: "costmap_2d::InflationLayer"}

  inflation:
    inflation_radius: 1.00 # default: 0.55
    cost_scaling_factor: 10.0 # default: 10.0
  static_map:
    unknown_cost_value: 0 # default: 0
    lethal_cost_threshold: 100 # default: 100
    map_topic: map
  obstacles:
    combination_method: 1
    max_obstacle_height: 3
    observation_sources: laser_scan
    map_type: costmap
    unknown_threshold: 2 # default: ~<name>/z_voxels
    mark_threshold: 0 # default: 0
    publish_voxel_map: true
    obstacle_range: 10.0                  # default: 2.5  
    raytrace_range: 11.0                  # default: 3.0 
    laser_scan:
      sensor_frame: laser                 
      topic: /scan               
      data_type: LaserScan                
      marking: true                       
      clearing: true

Here is the global costmap yaml:

 global_costmap:
  global_frame: map
  robot_base_frame: base_footprint

  update_frequency: 10.0
  publish_frequency: 10.0
  transform_tolerance: 0.5

  footprint: [[-0.765, -0.455], [-0.765, 0.455], [0.765, 0.455], [0.765, -0.455]]
  robot_radius: 0.15

  static_map: true  
  rolling_window: false

  plugins:
    - {name: static_layer, type: "costmap_2d::StaticLayer"}
    - {name: obstacle_layer, type: "costmap_2d::ObstacleLayer"}
    - {name: inflater_layer, type: "costmap_2d::InflationLayer"} 
  static_layer:
    unknown_cost_value: 0 # default: 0
    lethal_cost_threshold: 100 # default: 100
    map_topic: map # default: "map"

  obstacle_layer:
    combination_method: 1
    observation_sources: laser_scan
    map_type: costmap
    unknown_threshold: 2 # default: ~<name>/z_voxels
    mark_threshold: 0 # default: 0
    publish_voxel_map: true
    obstacle_range: 10 ...