feat: remove use_pointcloud_container

[kminoda]

Description

Remove use_pointcloud_container as discussed in https://github.com/orgs/autowarefoundation/discussions/4112.

• For individual node launcher such as lidar_centerpoint.launch.xml we leave the use_pointcloud_container interface as it is, so that we can launch the node itself without pointcloud_container.

MUST BE MERGED WITH:

• feat: remove use_pointcloud_container autoware_launch#806
• feat: remove use_pointcloud_container sample_sensor_kit_launch#87
• feat: remove use_pointcloud_container tier4/aip_launcher#200

Related links

• feat: remove use_pointcloud_container autoware_launch#806
• feat: remove use_pointcloud_container sample_sensor_kit_launch#87
• feat: remove use_pointcloud_container tier4/aip_launcher#200
• TIER IV INTERNAL LINK

Tests performed

• Launched Autoware and confirmed that it works fine

$ ros2 component list /pointcloud_container
  1  /perception/obstacle_segmentation/crop_box_filter                                                                                                                                                             
  2  /sensing/lidar/concatenate_data                                                                     
  3  /pointcloud_container/glog_component                                                                
  4  /perception/object_recognition/detection/voxel_grid_downsample_filter                                                                                                                                         
  5  /perception/occupancy_grid_map/occupancy_grid_map_node                                                                                                                                                        
  6  /perception/object_recognition/detection/clustering/low_height_crop_box_filter                                                                                                                                
  7  /perception/object_recognition/detection/centerpoint/lidar_centerpoint                                                                                                                                        
  8  /perception/obstacle_segmentation/common_ground_filter                                                                                                                                                        
  9  /perception/object_recognition/detection/voxel_based_compare_map_filter                                                                                                                                       
  10  /perception/object_recognition/detection/clustering/euclidean_cluster                                                                                                                                        
  11  /perception/obstacle_segmentation/occupancy_grid_map_outlier_filter 

Notes for reviewers

None

Interface changes

None

Effects on system behavior

None as long as you are using use_pointcloud_container = true. If you are using use_pointcloud_container = false, this PR will gather all the related nodes into one single container, resulting in less computational load.

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (7cb77dd) 14.86% compared to head (a188199) 14.42%.
Report is 2 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #6115      +/-   ##
==========================================
- Coverage   14.86%   14.42%   -0.45%     
==========================================
  Files        1845     1907      +62     
  Lines      126636   129584    +2948     
  Branches    37876    37545     -331     
==========================================
- Hits        18823    18687     -136     
- Misses      86655    89914    +3259     
+ Partials    21158    20983     -175     

Flag	Coverage Δ		*Carryforward flag
differential	∅ <ø> (?)
total	14.42% <ø> (-0.45%)	⬇️	Carriedforward from 2f941ac

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[miursh]

For sensing and perception part, LGTM

[kminoda]

@yukkysaito Would you review this PR?

[yukkysaito]

LGTM