engcang/SLAM-application resource
LeGO-LOAM, LIO-SAM, LVI-SAM, FAST-LIO2, Faster-LIO, VoxelMap, R3LIVE, Point-LIO, KISS-ICP, DLO, DLIO, Ada-LIO, PV-LIO, SLAMesh, ImMesh, FAST-LIO-MULTI, M-LOAM, LOCUS, SLICT, MA-LIO, CT-ICP, GenZ-ICP, iG-LIO, SR-LIO application and comparison on Gazebo and real-world datasets. Installation and config files are provided. observed · 2026-08-28
Health v2 · maintenance only
34/100
- Activity 4
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1946
- days_rel: n/a
- days_push: 579
- n_releases_24m: 0
Adoption not part of the score
1206 stars · 157 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A curated collection of installation guides, configuration files, and comparison results for many open-source LiDAR(-inertial) SLAM and odometry algorithms, tested on Gazebo simulation and real-world datasets. It bundles 20+ algorithms such as FAST-LIO2, LIO-SAM, and KISS-ICP with demo videos comparing their performance.
Use cases
- compare lidar slam algorithms before choosing one
- install and configure fast-lio2 or lio-sam on ros
- evaluate lidar inertial odometry on gazebo datasets
- find which slam method works in narrow tunnels or stairs
- set up multi-lidar odometry like fast-lio-multi
- learn slam algorithm differences with demo videos
When to choose
- you want to benchmark or compare existing SLAM/odometry algorithms side by side
- you need ready-made install and config files for many LiDAR SLAM packages
- you are evaluating which odometry approach fits your sensor setup (single/multi LiDAR, with/without IMU)
When to avoid
- you need a production-ready SLAM library itself - this is a comparison and setup guide, not an algorithm implementation
- you work with visual-only or 2D SLAM
- you need a non-ROS or Windows environment
Facets
learning-resource · maturity active
simulation robotics benchmarking robotics autonomous-vehicles simulation tutorials cpp slam lidar lidar-inertial-odometry gazebo ros comparison point-cloud linux
1 source
- readme: https://github.com/engcang/SLAM-application · fetched 2026-08-28 · 70ea024c6ba5
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| engcang/SLAM-application | main | 34 |
For agents
markdown · JSON · MCP: product_card(name="engcang/SLAM-application")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem