Path Planning: D*

[guilyx]

Summary

• Implement the original D* path planning algorithm (Stentz, 1994) — not D* Lite — with full RAISE/LOWER cost propagation, configurable heuristic weight for A*-like informed search, and incremental replanning when obstacles are injected at runtime.
• Add a two-GIF simulation: dstar_search.gif animates the grid-based search, obstacle injection (old path greys out), and replanned path; dstar_navigate.gif shows a car following the initial course via PurePursuit, then seamlessly switching to the replanned course when the dynamic obstacle appears.
• Add unit tests covering initial search (empty/gapped/blocked grids), replanning correctness, goal preservation, and heuristic efficiency; plus an integration test that runs the full simulation.

New files

File	Lines	Purpose
dstar_path_planner.py	Core D* algorithm: grid loading, backward search from goal, update_obstacles(), replan(), path extraction, visualization
dstar_path_planning.py	Simulation driver: builds grid, runs D*, injects dynamic obstacle, generates search GIF + car-following navigate GIF with _ReplanPurePursuit controller
dstar_search.gif	Search animation (7 phases: expand → path → hold → obstacle + grey → replan → new path → hold)
dstar_navigate.gif	Car navigation animation (PurePursuit switches course mid-drive)
test_dstar_path_planning.py	Integration/simulation test

Test plan

• pytest test/test_dstar_path_planning.py — simulation integration test
• python src/simulations/path_planning/dstar_path_planning/dstar_path_planning.py — visual check: both GIFs generate, search GIF shows greyed old path + green new path from start, navigate GIF shows car switching courses with correct red/grey path swap

[guilyx]

Need to fix obstacles, seems like I don't count inflation as an obstacle and I should.

[guilyx]

Need to fix obstacles, seems like I don't count inflation as an obstacle and I should.

Resolved