ompl/ompl
The Open Motion Planning Library (OMPL) observed · 2026-08-28
Health v2 · maintenance only
95/100
- Activity 99
- Release rhythm 86
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 73
- age_days: 4488
- days_rel: 19
- days_push: 7
- n_releases_24m: 4
Adoption not part of the score
2134 stars · 706 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
OMPL is an open-source C++ library of over 40 sampling-based motion planning algorithms (RRT-Connect, PRM, RRT*, KPIECE, etc.) across more than 20 state spaces, with Python bindings via Nanobind. It is deliberately decoupled from collision checking and visualization, making it the default planning backend in ROS/MoveIt and integrable into many robot software systems.
Use cases
- plan collision-free paths for robot arms
- compute motion plans for mobile robots
- plan paths for kinematically constrained manipulators
- benchmark and compare motion planning algorithms
- generate motion planning datasets for learning-based planners
- rapid millisecond replanning with SIMD-accelerated collision checking
- integrate motion planning into ROS/MoveIt pipelines
- prototype custom planners and state spaces in Python or C++
When to choose
- you need sampling-based motion planning for robots in C++ or Python
- you want a mature, well-tested planner library that integrates with ROS/MoveIt
- you need many planner algorithms and state spaces to experiment with or benchmark
- you need high-performance planning via the VAMP SIMD backend
- you are doing research on task and motion planning or learning for planning
When to avoid
- you need built-in collision checking, visualization, or robot kinematics (OMPL expects you to supply these)
- you need optimal control or trajectory optimization rather than sampling-based planning
- you need a turnkey robotics stack without ROS or simulator integration
- your project requires a permissive license without review (license is custom/non-standard)
Facets
library · maturity stable
simulation machine-learning benchmarking robotics autonomous-vehicles simulation windows cpp python cross-platform motion-planning sampling-based-planning rrt prm robotics vamp moveit collision-avoidance kinodynamic-planning algorithms linux macos
6 sources
- readme: https://github.com/ompl/ompl · fetched 2026-08-28 · fa7dc3d0bcd6
- homepage: https://ompl.kavrakilab.org · fetched 2026-08-29 · ef71f884b3cd
- site_page: https://ompl.kavrakilab.org/installation.html · fetched 2026-08-29 · 80e24c33cf16
- site_page: https://ompl.kavrakilab.org/FAQ.html · fetched 2026-08-29 · d9d7a9a0e2f2
- site_page: https://ompl.kavrakilab.org/integration.html · fetched 2026-08-29 · 13d4e14018a3
- site_page: https://ompl.kavrakilab.org/python.html · fetched 2026-08-29 · 3eb6a68390ef
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| ompl/ompl | main | 95 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem