# hku-mars/SUPER

Repository: https://github.com/hku-mars/SUPER
Canonical: https://ross.abutalabs.com/products/super
Language: C++
License Family: other
Last push: 2025-06-04T05:05:01+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 25, release rhythm 35, longevity 44
- inputs: {"age_days": 622, "days_push": 455, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1016, forks 154 (observed 2026-08-28T04:03:14.473756+00:00)

## What it is
SUPER is a safety-assured high-speed navigation system for micro aerial vehicles (MAVs), published in Science Robotics by HKU MaRS Lab. It provides a planning module supporting both ROS1 and ROS2, built around an efficient robocentric occupancy grid map for lidar-based motion planning.

## Use cases
- plan high-speed safe trajectories for drones
- navigate MAVs in unknown environments
- build occupancy grid maps from lidar for motion planning
- integrate ROS2 navigation planning into a drone stack
- reproduce research on safety-assured aerial navigation

## When to choose
- you need state-of-the-art high-speed navigation planning for aerial robots
- you work with ROS1 or ROS2 and lidar-based mapping
- you want to build on peer-reviewed robotics research with available hardware designs

## When to avoid
- you need ground-vehicle or indoor wheeled robot navigation out of the box
- you require a permissive license for commercial use (no license is specified)
- you need a plug-and-play solution without robotics/ROS expertise

## Facets
- artifact type: library
- maturity: active
- function: robotics, simulation, graphics
- domain: robotics, autonomous-vehicles, simulation
- platform: cpp
- tags: mav-navigation, motion-planning, lidar, occupancy-grid-map, ros1-ros2, drone, science-robotics, linux, ros

## Member repositories
- hku-mars/SUPER (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:14.473756+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 2026-08-30T07:11:18.887287+00:00, confidence not recorded.
  - readme: https://github.com/hku-mars/SUPER (fetched 2026-08-28T04:03:14.473756+00:00, sha a9bf007fe419)
- Data as of 2026-08-30T08:39:29.467469+00:00.