python-motion-planning
Motion planning algorithms for Python
Decision gist · record as of 2026-08-14
Yes, with conditions. Install if you need reference implementations of standard motion planning algorithms for research, education, or prototyping. The low install friction, active maintenance, and lack of known vulnerabilities support adoption. However, be aware of the GPLv3 copyleft requirement if you plan to integrate this into proprietary code, and verify that the specific algorithms you need are present in version 2.0.1 (some have not been migrated from earlier releases).AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with a pure Python wheel.
- Active maintenance with recent commits; last release 73 days ago.
- Depends on 9 runtime packages including numpy, scipy, numba for computation and matplotlib, pyvista for visualization.
License · maintenance · safety
copyleft license (copyleft) — Licensed under GPLv3 (copyleft). Any modifications or derivative works must be released under the same license and source code must be made available to users.
last release 2026-06-02 (73 days) · last repo commit 2026-06-02 · 1,072 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 127,226 downloads/mo, #11,750 on PyPI
Alternatives
Verify before relying
pip install python-motion-planning
import python_motion_planning
# Access path planners, controllers, and trajectory optimizers via submodules- Whether specific planner implementations (Dijkstra, A*, RRT, etc.) are fully functional in current version or partially migrated
- Performance characteristics and scalability limits for N-D planning problems
- Compatibility with specific robot simulation environments beyond the toy 2D simulator mentioned
What it is and what it does
Python Motion Planning provides a collection of motion planning implementations for robotics, organized into three main components: path planners that find collision-free routes on N-D grids using graph search (Dijkstra, A*, JPS, Theta*) and sampling-based methods (RRT, RRT*); trajectory optimizers that generate smooth curves respecting kinematic and dynamic constraints; and path-tracking controllers (Pure Pursuit, PID, DWA, APF) that guide robots along planned paths. It includes a matplotlib-based visualizer and a toy 2D physics simulator for testing controllers on circular and differential-drive robots.
The package targets roboticists and autonomous systems developers who need reference implementations of standard planning algorithms. It depends on numpy, scipy, and numba for numerical computation, matplotlib and pyvista for visualization, and gymnasium for environment interaction. The repository is actively maintained with recent updates, though some algorithms from earlier versions (LQR, MPC, evolutionary methods) have not been migrated to the current release.
Use it for
- Prototyping path-planning solutions for mobile robots in obstacle-filled environments
- Testing trajectory optimization and smoothing techniques for motion control
- Learning and teaching motion planning algorithms with working reference implementations
- Simulating multi-robot coordination using the toy 2D simulator with multiple robot types
- Benchmarking different planner algorithms on 2D and 3D grid problems
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Install if you need reference implementations of standard motion planning algorithms for research, education, or prototyping. The low install friction, active maintenance, and lack of known vulnerabilities support adoption. However, be aware of the GPLv3 copyleft requirement if you plan to integrate this into proprietary code, and verify that the specific algorithms you need are present in version 2.0.1 (some have not been migrated from earlier releases).
Install
python-motion-planning on PyPI
Before you install
Low install friction with a pure Python wheel. Active maintenance with recent commits; last release 73 days ago. Depends on 9 runtime packages including numpy, scipy, numba for computation and matplotlib, pyvista for visualization.
License in practice
Licensed under GPLv3 (copyleft). Any modifications or derivative works must be released under the same license and source code must be made available to users.
Quickstart
pip install python-motion-planning
import python_motion_planning
# Access path planners, controllers, and trajectory optimizers via submodulesVerify before relying
- Whether specific planner implementations (Dijkstra, A*, RRT, etc.) are fully functional in current version or partially migrated
- Performance characteristics and scalability limits for N-D planning problems
- Compatibility with specific robot simulation environments beyond the toy 2D simulator mentioned
Package facts
| License | copyleft license copyleft |
| Python support | Supports the current Python release >=3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagesnumpynumbascipymatplotlibosqpgymnasiumfaiss-cpupyvistapyvistaqt |
| Maintenance | Actively maintained 73 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 127,226 / month, #11,750 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: GNU General Public License v3 (GPLv3)Programming Language :: Python :: 3Programming Language :: Python :: 3 :: Only |
Evidence: python_motion_planning-2.0.1-py3-none-any.whl
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