feat(autoware_probabilistic_occupancy_grid_map): cuda accelerated implementation

[knzo25]

Description

This PR introduces a CUDA accelerated version of the OGM.
Several improvements are possible, but this PR attempts to replicate whenever possible all the functionalities of the original OGM that were actively used.

Algorithms that were not reimplemented in CUDA:

• extractCommonPointCloud: this option was off in all configs and launchers, and talking with @YoshiRi, it would not be used

Algorithms that were not tested:

• Fusion. No project actively uses it, but it should work since it uses a non accelerated version

Related links

Parent Issue:

• Link

How was this PR tested?

Tested with our internal reference design. The OGM will not give the exact same results, but visual inspection shows almost the same characteristics.
The latency with a VLS128 goes from ~20ms to 2-3ms

Notes for reviewers

@soblin
This PR introduces CUDA dependencies. If this would break any P/C workflows, please let me know and I will try to make a version that works even without CUDA installes (sadly, via macros).

In addition, I was told that I should not accelerate the laserscan method. If this is wrong , please let me know

None.

Interface changes

None.

Effects on system behavior

None.

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[knzo25]

Note to self: run this with the evaluator

[knzo25]

@YoshiRi
Using CUDA we can delete the 2 subsample filters from the raw and obstacle pointcloud. Would you prefer a different PR for that?

@soblin
Here or internally, can you give a few pointers on how to check that I did not break the laserscan method?

[youtalk]

This does not seem to be caused by the Autoware development container.

https://github.com/autowarefoundation/autoware.universe/actions/runs/12150740163/job/33884090279?pr=9542#step:5:7660

Error: ponent_container-1] [ERROR] [1733273274.264398228] [occupancy_grid_map_container]: Component constructor threw an exception: cudaErrorInsufficientDriver (35)@/__w/autoware.universe/autoware.universe/install/autoware_cuda_utils/include/autoware/cuda_utils/cuda_unique_ptr.hpp#L43: CUDA driver version is insufficient for CUDA runtime version

The error indicates that the CUDA runtime library is missing when loading into the component container during execution.
Therefore, it is believed that referencing other CUDA-dependent packages and modifying the component loading should resolve the issue.

[knzo25]

@youtalk
In the past and in my own environment, I had only seen that issue when I messed up my environment (cuda and driver installations).

I tried using the docker environment
https://autowarefoundation.github.io/autoware-documentation/main/installation/autoware/docker-installation/

and ran:

colcon test --packages-select autoware_probabilistic_occupancy_grid_map
colcon test

with no errors (to the relevant package). Should I expect the CI/CD to pass build and test if it works in autoware's docker installation?

[soblin]

@knzo25 Sorry I noticed your comments. For P/C workflow, no worry.

[soblin]

@knzo25 For testing laserscan method, run

ros2 launch autoware_launch planning_simulator.launch.xml map_path:=<> vehicle_model:=<> sensor_model:=<> 

, then place ego and a NPC, and visualize the OccupancyGridMap (you can find the checkbox under perception). And check if the region behind of NPC from ego is gray

[YoshiRi]

@knzo25

Using CUDA we can delete the 2 subsample filters from the raw and obstacle pointcloud. Would you prefer a different PR for that?

You mean we can remove obstacle pointcloud filtering with raw data I explained last Friday?
If it is not complicated, I think it's okay to include that feature within this PR.

[knzo25]

@YoshiRi
I mean, we can delete the Pickup subsample (the extra node). It takes about 10ms for the raw pointcloud currently. If we forego that one, of course, the new implementation will be a bit slower, but not 10ms (sorry, I haven't had the chance to provide all the evidence required here 🙇 )

[technolojin]

Except the conflict, this PR worked in my local environment.

[technolojin]

I accidentally pushed (-forced) into your repo. I am sorry for this.
The changes are resolving the conflict and update relatively latest main(rebase).

[YoshiRi]

It worked on my environment. I left some trivial comments to fix.

[YoshiRi]

for safety, how about using epsilon?

std::abs(dist) < epsilon

[knzo25]

Addressed in 5c14fc0
(this was essentially a copy from the upstream)

[YoshiRi]

[imho]
Add index check for safety

if(dm_index >= dm_size_x * dm_size_y) return;

[knzo25]

Addressed in ea46130

[codecov]

Codecov Report

Attention: Patch coverage is 0% with 343 lines in your changes missing coverage. Please review.

Project coverage is 29.73%. Comparing base (874dbdd) to head (263feab).
Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
...id_map/lib/costmap_2d/occupancy_grid_map_fixed.cpp	0.00%	51 Missing ⚠️
...p/lib/costmap_2d/occupancy_grid_map_projective.cpp	0.00%	47 Missing ⚠️
...rid_map/lib/costmap_2d/occupancy_grid_map_base.cpp	0.00%	44 Missing ⚠️
...costmap_2d/occupancy_grid_map_projective_kernel.cu	0.00%	38 Missing ⚠️
.../lib/costmap_2d/occupancy_grid_map_fixed_kernel.cu	0.00%	28 Missing ⚠️
...id_map/lib/updater/binary_bayes_filter_updater.cpp	0.00%	21 Missing ⚠️
...istic_occupancy_grid_map/lib/utils/utils_kernel.cu	0.00%	20 Missing ⚠️
...p/src/fusion/synchronized_grid_map_fusion_node.cpp	0.00%	19 Missing ⚠️
...d_map/pointcloud_based_occupancy_grid_map_node.cpp	0.00%	17 Missing ⚠️
...istic_occupancy_grid_map/utils/cuda_pointcloud.hpp	0.00%	13 Missing ⚠️
... and 10 more

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #9542      +/-   ##
==========================================
- Coverage   29.82%   29.73%   -0.09%     
==========================================
  Files        1433     1441       +8     
  Lines      108060   107983      -77     
  Branches    42965    42777     -188     
==========================================
- Hits        32226    32110     -116     
- Misses      72705    72762      +57     
+ Partials     3129     3111      -18     

Flag	Coverage Δ		*Carryforward flag
differential-cuda	0.00% <0.00%> (?)
total	29.83% <ø> (+0.01%)	⬆️	Carriedforward from 4c13bb0

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

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[knzo25]

@soblin
Tested that adding a pedestrian in the planning sim has the expected behavior

[YoshiRi]

LGTM