Skip to content

[codex] Add GPU kinodynamic graph-neural MPPI demo #103

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
rsasaki0109 merged 1 commit into from
May 25, 2026
Merged

[codex] Add GPU kinodynamic graph-neural MPPI demo #103

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 4 additions & 0 deletions CMakeLists.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -451,6 +451,10 @@ add_executable(gpu_graph_guided_neural_mppi src/gpu_graph_guided_neural_mppi.cu)
target_link_libraries(gpu_graph_guided_neural_mppi ${OpenCV_LIBS})
target_compile_options(gpu_graph_guided_neural_mppi PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--expt-relaxed-constexpr>)

add_executable(gpu_kinodynamic_graph_neural_mppi src/gpu_kinodynamic_graph_neural_mppi.cu)
target_link_libraries(gpu_kinodynamic_graph_neural_mppi ${OpenCV_LIBS})
target_compile_options(gpu_kinodynamic_graph_neural_mppi PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--expt-relaxed-constexpr --use_fast_math>)

add_executable(gpu_interaction_graph_risk src/gpu_interaction_graph_risk.cu)
target_link_libraries(gpu_interaction_graph_risk ${OpenCV_LIBS})
target_compile_options(gpu_interaction_graph_risk PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--expt-relaxed-constexpr>)
Expand Down
Binary file added gif/gpu_kinodynamic_graph_neural_mppi.gif
View file
Open in desktop
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
7 changes: 4 additions & 3 deletions readme.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ Same algorithm on CPU and GPU — GPU enables orders of magnitude more particles
| Clustering / graph ML | `gpu_em_gmm`, `gpu_spectral_clustering`, `gpu_label_propagation`, `gpu_label_propagation_traversability`, `gpu_graph_crf_traversability` | 262K GMM points / 3K graph nodes | 90.2x EM; 193x spectral; 123x propagation; 106x CRF |
| Black-box optimization | `gpu_cma_es` | 3 x 32,768 candidates x 10D | 1,254x objective eval |
| Monte Carlo planning | `gpu_mcts_planner` | 64 scenes x 4096 rollouts x 48 horizon | 712x vs CPU |
| Learning-based planning | `gpu_diffusion_planner`, `gpu_diffusion_policy`, `gpu_diff_value_iteration_traversability`, `gpu_neural_astar_traversability`, `gpu_anytime_neural_astar_traversability`, `gpu_multigoal_neural_astar_traversability`, `gpu_spatiotemporal_neural_astar_traversability`, `gpu_experience_graph_neural_planner`, `gpu_graph_guided_neural_mppi` | 512 x 64 trajectories / 192x128 soft VI / 64x neural A* / 1536-node graph / 32768 MPPI rollouts | analytic score -> BC denoising policy; 747.4x learned-cost VI; 153.1x batched neural A*; 278.5x experience-graph A*; 1320.1x graph-guided MPPI |
| Learning-based planning | `gpu_diffusion_planner`, `gpu_diffusion_policy`, `gpu_diff_value_iteration_traversability`, `gpu_neural_astar_traversability`, `gpu_anytime_neural_astar_traversability`, `gpu_multigoal_neural_astar_traversability`, `gpu_spatiotemporal_neural_astar_traversability`, `gpu_experience_graph_neural_planner`, `gpu_graph_guided_neural_mppi`, `gpu_kinodynamic_graph_neural_mppi` | 512 x 64 trajectories / 192x128 soft VI / 64x neural A* / 1536-node graph / 32768 MPPI rollouts | analytic score -> BC denoising policy; 747.4x learned-cost VI; 153.1x batched neural A*; 278.5x experience-graph A*; 1320.1x graph-guided MPPI; 49.9x kinodynamic graph MPPI |
| Voxel map (3D) | `comparison_voxel_map` | 256x256x32 | 58x per ray |
| ESDF (2D/3D) | `comparison_esdf`, `comparison_esdf_3d` | 640K cells / 1.05M voxels | 53,404x / 86,613x |
| LiDAR sim | `comparison_lidar_sim`, `comparison_lidar3d_sim`, `comparison_lidar3d_realistic` | 1M 2D / 131K 3D rays | + 5 physical effects (realistic) |
Expand Down Expand Up @@ -80,8 +80,8 @@ Same algorithm on CPU and GPU — GPU enables orders of magnitude more particles
| <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_anytime_neural_astar_traversability.gif" width="400"/> | <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_multigoal_neural_astar_traversability.gif" width="400"/> |
| **GPU spatiotemporal neural A* traversability (moving obstacle risk, max risk 1.94 -> 0.26, 106.5x vs CPU)** | **GPU learned experience graph planner (128 × 1536-node graph A*, 51.8% fewer expansions, 278.5x vs CPU)** |
| <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_spatiotemporal_neural_astar_traversability.gif" width="400"/> | <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_experience_graph_neural_planner.gif" width="400"/> |
| **GPU graph-guided neural MPPI (32768 rollouts × H=72, cost 1430.31 -> 842.35, terminal 1.25 -> 0.15, 1320.1x vs CPU)** | |
| <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_graph_guided_neural_mppi.gif" width="400"/> | |
| **GPU graph-guided neural MPPI (32768 rollouts × H=72, cost 1430.31 -> 842.35, terminal 1.25 -> 0.15, 1320.1x vs CPU)** | **GPU kinodynamic graph-neural MPPI (32768 nonholonomic rollouts × H=72, cost 1516.74 -> 851.11, terminal 5.11 -> 0.88, 49.9x vs CPU)** |
| <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_graph_guided_neural_mppi.gif" width="400"/> | <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_kinodynamic_graph_neural_mppi.gif" width="400"/> |
| **GPU Multi-Robot Planner (200 robots, parallel BF distance fields)** | **Massive Collision Check (1M segments, 1,277x)** |
| <img src="https://rsasaki0109.github.io/CudaRobotics/gpu_multi_robot_planner.gif" width="400"/> | <img src="https://rsasaki0109.github.io/CudaRobotics/comparison_collision_check.gif" width="400"/> |
| **Massive RRT* Rewire (CPU 2K vs CUDA 200K nodes)** | **3D ESDF (32³ CPU vs 128²×64 CUDA, 86,613x)** |
Expand Down Expand Up @@ -198,6 +198,7 @@ cd ros2_ws && colcon build --packages-select cuda_robotics
| GPU spatiotemporal neural A* traversability | 64 batched 192x128 dynamic-risk neural A* queries, moving-obstacle max risk 1.94 -> 0.26, 80.9% fewer expansions than dynamic Dijkstra, **106.5x** vs CPU sequential spatiotemporal A* |
| GPU learned experience graph planner | 128 batched 1536-node learned experience-graph A* queries, all queries reachable, 51.8% fewer expansions than graph Dijkstra, **278.5x** vs CPU sequential graph A* |
| GPU graph-guided neural MPPI | 32768 rollouts x H=72 x guided/unguided batches, cost 1430.31 -> 842.35, terminal error 1.25 -> 0.15, route error 0.491 -> 0.045, **1320.1x** vs CPU equivalent rollout evaluation |
| GPU kinodynamic graph-neural MPPI | 32768 nonholonomic speed/steering rollouts x H=72 x guided/unguided batches, cost 1516.74 -> 851.11, terminal error 5.11 -> 0.88, route error 1.530 -> 0.252, **49.9x** vs CPU equivalent kinodynamic rollout evaluation |
| GPU GNN swarm controller | 2048 agents x 3 message passes, 2.88 ms/control, **44.3x** vs CPU |
| GPU reciprocal risk planner | 1024 agents x 9 actions x H=16, 4.05 ms/plan, **311.5x** vs CPU |
| GPU assignment tracking | 128 scenes x 48 tracks x 72 detections, **14.0x** vs CPU |
Expand Down
Loading
Loading