# ZJU-FAST-Lab/ego-planner

Repository: https://github.com/ZJU-FAST-Lab/ego-planner
Canonical: https://ross.abutalabs.com/products/ego-planner
Language: C++
License: GPL-3.0
License Family: copyleft
Last push: 2025-03-08T09:23:46+00:00

## Health v2 (maintenance only)
Score: 37/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 10, release rhythm 35, longevity 100
- inputs: {"age_days": 2306, "days_push": 543, "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 2618, forks 405 (observed 2026-08-28T04:07:04.721370+00:00)

## What it is
EGO-Planner is a lightweight, ESDF-free gradient-based local trajectory planner for quadrotors, implemented in C++ on ROS. It computes collision-free trajectories in roughly 1 ms without building a Euclidean Signed Distance Field.

## Use cases
- plan collision-free trajectories for a quadrotor drone
- run fast local replanning on a UAV in cluttered environments
- avoid building ESDF maps for drone obstacle avoidance
- simulate quadrotor navigation in ROS with obstacle maps
- research benchmark for gradient-based drone planners

## When to choose
- you need millisecond-scale local planning for a single quadrotor
- you want an ESDF-free planner that runs on resource-constrained onboard hardware
- you are doing academic research on aerial robotics and want a well-cited baseline

## When to avoid
- you need multi-drone swarm planning - use EGO-Swarm instead
- you need global path planning rather than local replanning
- your project is not ROS-based or not on Linux

## Facets
- artifact type: library
- maturity: stable
- function: simulation, robotics
- domain: robotics, autonomous-vehicles
- platform: cpp
- tags: quadrotor, motion-planning, trajectory-optimization, esdf-free, ros, drones, local-planner, algorithms, linux

## Member repositories
- ZJU-FAST-Lab/ego-planner (main) score 37

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:04.721370+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 2026-08-30T02:20:16.955561+00:00, confidence not recorded.
  - readme: https://github.com/ZJU-FAST-Lab/ego-planner (fetched 2026-08-28T04:07:04.721370+00:00, sha 6144494a33cb)
- Data as of 2026-08-30T08:39:29.467469+00:00.