# PythonRobotics: d star lite

Official PythonRobotics python main example for d star lite. Inspect the pinned source and upstream setup before use.

ID: `pythonrobotics-pathplanning-dstarlite-d-star-lite-py`

Record version: `source-6802cd6c96d75ddd8219d7998bf71bbf04268b96e667b5e46b9a80d9bc5b4f6c`

Hub commit: `bee2df6672c145beeff064d2a203cebdbd3c5bf3`

## Access

Fetch the pinned repository, verify this source checksum, and use upstream installation and invocation. This record does not install or execute code.

Optional inert file retrieval: `python /PATH_TO_SKILL/scripts/rsh.py fetch-source pythonrobotics-pathplanning-dstarlite-d-star-lite-py --expected-source-revision cdd0cc888802b584c2d654ca85e3c5460973487d --expected-source-sha256 6802cd6c96d75ddd8219d7998bf71bbf04268b96e667b5e46b9a80d9bc5b4f6c --project ./experiment --json`. This verifies one file, preserves provenance and never installs or runs it. See [source-file retrieval](https://hub.superfastrobotics.com/source-files.md).

Hub preparation adapter: **false**. Runtime verification: **not_run**.

Upstream setup: https://github.com/AtsushiSakai/PythonRobotics/blob/cdd0cc888802b584c2d654ca85e3c5460973487d/README.md

## Source and license

- Repository: https://github.com/AtsushiSakai/PythonRobotics
- Pinned source: https://github.com/AtsushiSakai/PythonRobotics/blob/cdd0cc888802b584c2d654ca85e3c5460973487d/PathPlanning/DStarLite/d_star_lite.py
- Revision: `cdd0cc888802b584c2d654ca85e3c5460973487d`
- Path: `PathPlanning/DStarLite/d_star_lite.py`
- Source SHA256: `6802cd6c96d75ddd8219d7998bf71bbf04268b96e667b5e46b9a80d9bc5b4f6c`
- Source bytes: 16563
- Original authors: vss2sn
- License: [MIT](https://github.com/AtsushiSakai/PythonRobotics/blob/cdd0cc888802b584c2d654ca85e3c5460973487d/LICENSE)
- License scope: Selected PythonRobotics algorithm demonstration source under the pinned MIT license text, Copyright (c) 2016 - now Atsushi Sakai and other contributors. Preserve repository license and each selected file's author notices. This is source-text scope only; dependencies, mathematical references, generated plots and any external assets retain separate terms. GitHub's automated classifier reports NOASSERTION; the MIT identity here comes from the exact reviewed LICENSE bytes, not that classifier.

License SHA256: `ca6f10832a25c1cd07fa62872458ca336a6ea83ee2f2236216086bd7a5bbf264`

## Requirements

```json
{
  "python": "Upstream README and requirements/environment.yml declare Python 3.13.x; no interpreter/package combination was installed or tested.",
  "packages": [
    "matplotlib==3.11.2 (repository requirements declaration; all five scripts import pyplot)",
    "numpy==2.5.3 (repository requirements declaration; four selected entrypoints import numpy)",
    "scipy==1.18.1 (repository requirements declaration; Hybrid A* imports scipy.spatial)",
    "cvxpy==1.9.3 (repository requirements declaration; selected MPC source only, which calls solver=cvxpy.CLARABEL)",
    "ecos==2.0.14 (repository requirements declaration; not substituted for the selected MPC source's CLARABEL solver)",
    "Matching pinned in-repository helpers for Hybrid A* and MPC; this individual source-file reference is not a full runnable bundle"
  ],
  "display": "Mathematical planning/tracking demonstrations with hard-coded maps, goals and simulated dynamics; no hardware controller or exact robot model is identified. Matplotlib animation is enabled in source and requires suitable display/backend configuration. A*/D* Lite/DWA imports are stdlib/Matplotlib/NumPy; Hybrid A* also imports local dynamic_programming_heuristic, car, ReedsSheppPath.reeds_shepp_path_planning and SciPy; MPC imports utils.angle, PathPlanning.CubicSpline.cubic_spline_planner and cvxpy/CLARABEL. Use the exact upstream checkout/layout and read its setup. Dependency versions and optional GUI/solver support are declarations, not verified runtime compatibility.",
  "execution_domain": "computation-or-algorithm-simulation",
  "source_imports": [
    "math",
    "matplotlib.pyplot",
    "numpy",
    "random"
  ]
}
```

## Invocation

```json
{
  "entrypoint": "python PathPlanning/DStarLite/d_star_lite.py",
  "notes": "Run the selected Python main only after independent upstream dependency, GUI/backend and local-helper setup review. These are numerical algorithm demonstrations, not commands for physical robots or ready deployment policies. The repository recommends pip requirements/requirements.txt or conda requirements/environment.yml; those are upstream declarations and were not executed. Keep the exact checkout layout for local imports. Five sources were only read, hashed and parsed; no Hub adapter, installation, simulation result, robot-model support or compatible runtime combination is asserted."
}
```

## Compatibility

```json
[]
```

Missing environment fields remain unknown. Source discovery labels do not establish robot compatibility.

## Evidence

Level: **source_reviewed**. Runtime verification: **not_run**.

Fetched and SHA-256 checked this immutable source; statically parsed Python or located native main; verified pinned license bytes and checked explicit per-file license identifiers. No upstream code executed.

Source review and contributor reports do not establish task completion. Preserve upstream attribution and licenses.