# HKUST-Aerial-Robotics/Teach-Repeat-Replan

Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments

Repository: https://github.com/HKUST-Aerial-Robotics/Teach-Repeat-Replan
Canonical: https://ross.abutalabs.com/products/teach-repeat-replan
Language: C++
License: GPL-3.0
License Family: copyleft
Topics: autonomous-navigation, uav, motion-planning, autonomous-drone-race, aerial-robotics, perception
Last push: 2021-10-19T06:33:31+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2626, "days_push": 1779, "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 1157, forks 265 (observed 2026-08-28T04:03:48.292869+00:00)

## What it is
Teach-Repeat-Replan is a complete C++/ROS system enabling aggressive autonomous drone flight in complex environments. It converts a manually taught (demonstrated) trajectory into a smooth, safe repeating trajectory with local replanning to avoid unmapped or moving obstacles.

## Use cases
- autonomous drone racing
- repeat a manually flown drone trajectory safely
- aggressive UAV flight in cluttered environments
- avoid unmapped or moving obstacles during flight
- infrastructure inspection with aerial robots
- search-and-rescue drone missions
- trajectory replanning for quadrotors

## When to choose
- you need a full teach-and-repeat pipeline for UAV aggressive flight
- you want smooth, safe trajectory generation from jerky human-taught paths
- you are doing research on drone racing or aerial robotics replanning

## When to avoid
- you need a simple waypoint-following autopilot without replanning
- your platform is not ROS-based or not a multirotor UAV
- you need a maintained product with recent updates and support

## Facets
- artifact type: application
- maturity: maintenance
- function: robotics, simulation, machine-learning, developer-tools
- domain: robotics, autonomous-vehicles, simulation
- platform: cpp
- tags: uav, motion-planning, drone-racing, teach-and-repeat, trajectory-optimization, ros, linux

## Member repositories
- HKUST-Aerial-Robotics/Teach-Repeat-Replan (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.292869+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 2026-08-30T06:32:00.379424+00:00, confidence not recorded.
  - readme: https://github.com/HKUST-Aerial-Robotics/Teach-Repeat-Replan (fetched 2026-08-28T04:03:48.292869+00:00, sha 9d6a3e3ad942)
- Data as of 2026-08-30T08:39:29.467469+00:00.