feat(ndt_scan_matcher): dynamic map loading

[kminoda]

Signed-off-by: kminoda [email protected]

Description

I would like to add a dynamic map loading functionality option for ndt_scan_matcher.

In order to pass the build CI, we first need to merge

• feat(ndt_omp): add multigrid_ndt_omp for dynamic map loading  tier4/ndt_omp#19

Must be merged with

• feat(autoware_launch): add NDT parameters for dynamic_map_loading autoware_launch#151

NOTE:
This PR will replace current ndt_omp with multigrid_ndt_omp, which is a customized version for dynamic map loading feature. Although most of the interfaces prepared in ndt_omp can also be used in multigrid_ndt_omp, there are one difference:

• multigrid_ndt_omp does not have neighborhood_search_method option, since we currently do not implement search method other than kd-tree.

Thus, do NOTE that neighborhood_search_method parameter in ndt_scan_matcher is also removed in this PR.

Related links

• https://github.com/orgs/autowarefoundation/discussions/2696

• https://github.com/orgs/autowarefoundation/discussions/2812

Tests performed

I tested with a data from Autoware tutorial. The map is divided into 20m grids (sample-map-rosbag_split.zip).

• I have confirmed that the Autoware performs the same as the current Autoware when use_dynamic_map_loading is set false.
• I have confirmed the following when use_dynamic_map_loading is set true.
  • localization performance does not change
  • map is dynamically loaded in ndt_scan_matcher (see /localization/pose_estimator/debug/loaded_pointcloud_map)

In addition, we, TIER IV, have confirmed that the computational resource required for dynamic map loading is low enough for several TIER IV vehicles, based on a several experiments with real hardware.

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[KYabuuchi]

I have tried all combinations of parameters and verified that the node works according to this table. 👍

[KYabuuchi]

Since the PR about autoware_launch will change the config of map_loader, can you also match the config in this PR as follows?

[codecov]

Codecov Report

Base: 11.37% // Head: 11.35% // Decreases project coverage by -0.02% ⚠️

Coverage data is based on head (1503f7d) compared to base (0305906).
Patch coverage: 0.00% of modified lines in pull request are covered.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2339      +/-   ##
==========================================
- Coverage   11.37%   11.35%   -0.02%     
==========================================
  Files        1277     1278       +1     
  Lines       89317    89625     +308     
  Branches    23653    23681      +28     
==========================================
+ Hits        10160    10179      +19     
- Misses      68386    68665     +279     
- Partials    10771    10781      +10     

Flag	Coverage Δ		*Carryforward flag
differential	12.45% <0.00%> (?)
total	11.37% <0.00%> (ø)		Carriedforward from 0305906

*This pull request uses carry forward flags. Click here to find out more.

Impacted Files	Coverage Δ
...ization/ndt_scan_matcher/src/map_update_module.cpp	0.00% <0.00%> (ø)
...ion/ndt_scan_matcher/src/ndt_scan_matcher_core.cpp	0.00% <0.00%> (ø)
planning/static_centerline_optimizer/src/utils.cpp	33.33% <0.00%> (+4.58%)	⬆️

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[kminoda]

@KYabuuchi Thanks! You're right. Resolved here: de0ef18

@RyuYamamoto Since a parameter in map_loader has been modified in this PR, would you also review the change?

[kminoda]

@yukkysaito @KYabuuchi @YamatoAndo
FYI: I disabled dynamic map loading by default, since there exists a case where this setting may harm Autoware system.
(Especially the case when the given map is divided into some large grids, e.g. 1000m x 1000m.)

[kminoda]

@yukkysaito @KYabuuchi @YamatoAndo
FYI: After a short discussion with Saito-san, I enabled dynamic map loading by default, again.

The reason is because we can continuously test this new feature by enabling it by default.
(Furthermore, we can avoid the above-mentioned risk, which is the case when the user provide largely divided maps, by properly setting the requirements)

[yukkysaito]

@kminoda Thank you 👍 could you please note any restrictions in the readme?

[kminoda]

@RyuYamamoto Friendly ping for review 🙇

[RyuYamamoto]

LGTM