# HKUST-Aerial-Robotics/A-LOAM

Advanced implementation of LOAM

Repository: https://github.com/HKUST-Aerial-Robotics/A-LOAM
Canonical: https://ross.abutalabs.com/products/a-loam
Language: C++
License: NOASSERTION
License Family: other
Topics: loam, lidar, slam
Last push: 2023-10-19T11:18:59+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": 2737, "days_push": 1049, "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 2438, forks 831 (observed 2026-08-28T04:06:51.547695+00:00)

## What it is
A-LOAM is an advanced, simplified C++ implementation of LOAM (Lidar Odometry and Mapping in Real-time) built on Eigen and Ceres Solver. It performs real-time lidar odometry and mapping and serves as clean learning material for SLAM beginners.

## Use cases
- run real-time lidar odometry and mapping with a Velodyne VLP-16 or HDL-64
- evaluate SLAM on the KITTI odometry dataset
- learn how LOAM-style lidar SLAM works from clean, readable code
- process rosbag recordings of indoor and outdoor environments into 3D maps
- build a lidar SLAM pipeline quickly using Docker without environment setup pain

## When to choose
- you need a well-known, real-time lidar odometry and mapping baseline
- you are a SLAM beginner wanting a simple, readable LOAM implementation
- you work with Velodyne lidars and ROS on Ubuntu
- you want a Docker-based reproducible SLAM setup

## When to avoid
- you need visual-inertial or multi-sensor fusion SLAM
- your project targets Windows, macOS, or non-ROS environments
- you need actively maintained code with recent feature development
- you require a custom lidar not supported by the provided launch configurations

## Facets
- artifact type: library
- maturity: maintenance
- function: simulation, computer-vision, robotics
- domain: robotics, autonomous-vehicles
- platform: cpp
- tags: lidar, slam, odometry, point-cloud, loam, ros, ceres-solver, pcl, mapping, algorithms, linux

## Member repositories
- HKUST-Aerial-Robotics/A-LOAM (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:51.547695+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 2026-08-30T02:30:46.613340+00:00, confidence not recorded.
  - readme: https://github.com/HKUST-Aerial-Robotics/A-LOAM (fetched 2026-08-28T04:06:51.547695+00:00, sha 290a41c0a0d1)
- Data as of 2026-08-30T08:39:29.467469+00:00.