OMPL: Rigid Body Planning With Controls

Official OMPL python main example for Rigid Body Planning With Controls. Inspect the pinned source and upstream setup before use.

ompl-demos-rigidbodyplanningwithcontrols-py | Record version: source-b9b7e0de41fa6cce61049030bde6232b20b74983a254ee97a73c3d1682fe530f

Record JSON | Markdown | Pinned upstream source

Access

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

Hub preparation adapter: false. Follow the upstream setup and invocation contract.

Source and license

Repository: https://github.com/ompl/ompl
Revision: 1ae6ac0bf7e9cb67d8994a8b8742833f813fdd39
Path: demos/RigidBodyPlanningWithControls.py
Source SHA256: b9b7e0de41fa6cce61049030bde6232b20b74983a254ee97a73c3d1682fe530f
Original authors: See pinned upstream source and license notices.
License: BSD-3-Clause
License scope: Selected example source code only; preserve upstream copyright and per-file notices. Robot models, datasets, weights, simulator binaries and third-party dependencies retain their separate licenses.
License SHA256: f1b0b41dbea7d46f34a723e827b5ef50070d006b34d5463f77a0a06d3dccdf2d
Hub commit: 88022cc5fa2396f47b1f2354e988189dc8e53bea

Requirements

{
  "python": "Python/C++ toolchain compatible with pinned OMPL 2.0.2",
  "packages": [
    "OMPL 2.0.2 pinned source",
    "CMake/compiler and optional Python bindings/dependencies per selected demo"
  ],
  "display": "Build the selected native demo target or install matching Python bindings. Planning demos need their state-space/validity assumptions and optional meshes/data; a solution path is not automatically a controller.",
  "execution_domain": "computation-or-simulation",
  "source_imports": [
    "functools",
    "math",
    "ompl"
  ]
}

Invocation

{
  "entrypoint": "python demos/RigidBodyPlanningWithControls.py",
  "notes": "Build the selected native demo target or install matching Python bindings. Planning demos need their state-space/validity assumptions and optional meshes/data; a solution path is not automatically a controller. No Hub preparation adapter or measured runtime success is claimed."
}

Explicit compatibility

[]

Missing environment fields remain unknown. 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.