# zhm-real/PathPlanning

Common used path planning algorithms with animations.

Repository: https://github.com/zhm-real/PathPlanning
Canonical: https://ross.abutalabs.com/products/pathplanning
Homepage: https://github.com/zhm-real/PathPlanning
Language: Python
License: MIT
License Family: permissive
Topics: astar, anytime-repairing-astar, learning-realtime-astar, realtime-adaptive-astar, lifelong-planning-astar, dstar, dstar-lite, anytime-dstar, rrt, rrt-star, rrt-connect, dynamic-rrt, extended-rrt, informed-rrt-star, fast-marching-trees, rrt-star-smart, batch-informed-trees, path-planning
Last push: 2023-02-06T07:54:46+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2269, "days_push": 1304, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 9345, forks 1770 (observed 2026-08-28T04:10:30.757325+00:00)

## What it is
A Python collection of common robotics path planning algorithms, covering search-based methods (Dijkstra, A* and variants, D* Lite) and sampling-based methods (RRT family, FMT*, BIT*), each with animated visualizations. It serves as an educational reference with links to the underlying papers.

## Use cases
- learn how A* and its variants work with visual animations
- compare RRT, RRT* and informed RRT* implementations
- prototype path planning for a robot navigation project
- study D* Lite and replanning algorithms for dynamic environments
- find reference implementations of sampling-based motion planners
- teach path planning algorithms in a robotics course

## When to choose
- you want readable, educational implementations of classic planners with visual feedback
- you need a reference to compare against your own planner implementation
- you are studying or teaching search-based and sampling-based planning algorithms

## When to avoid
- you need a production-grade, performant planner for a real robot
- you need 3D planning or integration with ROS out of the box
- you need actively maintained code with new features

## Facets
- artifact type: library
- maturity: maintenance
- function: simulation, developer-tools, data-visualization
- domain: robotics, simulation, education
- platform: python, cross-platform
- tags: path-planning, astar, rrt, motion-planning, robotics-algorithms, animations, search-algorithms, sampling-based-planning, algorithms

## Member repositories
- zhm-real/PathPlanning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:30.757325+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:22:27.368549+00:00, confidence not recorded.
  - readme: https://github.com/zhm-real/PathPlanning (fetched 2026-08-28T04:10:30.757325+00:00, sha 01bb68d1e0d3)
  - homepage: https://github.com/zhm-real/PathPlanning (fetched 2026-08-29T08:22:23.167773+00:00, sha e0bd27458b6d)
- Data as of 2026-08-30T08:39:29.467469+00:00.