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RTAB-Map

Perception · Perception & Vision Software

RTAB-Map

RTAB-Map 0.22·Université de Sherbrooke (IntRoLab)

Active Open source Real-time capable API available
CATEGORYPerception · Perception & Vision Software
READINESSTRL 9
ADOPTION SCALEIndustry Standard
LICENSESBSD-3-Clause
FIRST RELEASE2013

RTAB-Map (Real-Time Appearance-Based Mapping) is a mature open-source SLAM library developed since 2013 at IntRoLab, Université de Sherbrooke, by Mathieu Labbé and Prof. François Michaud. A distinctive feature is the hybrid approach: graph-based SLAM with appearance-based loop closure via bag-of-words, operating simultaneously on RGB-D, stereo, monocular, and 2D/3D LiDAR. BSD-3-Clause license.

RTAB-Map offers a rare combination in open-source: full dense mapping (point clouds + meshes), efficient memory management (memory management — moving old maps between WM ↔ STM ↔ LTM), full 3D occupancy grid (OctoMap integration), direct support for RViz 2 and Foxglove. It runs in three modes: SLAM (mapping + localization), localization-only (on a previously built map), and mapping-only.

Sensor support: Intel RealSense D435i/D455/L515, Microsoft Kinect/Azure Kinect, Stereolabs ZED 2i, Hesai/Velodyne/Ouster/Livox LiDAR, XSens/Bosch IMU. Full graph optimizers: g2o, GTSAM, cvsba. The rtabmap_ros package is officially supported across all ROS 1 distributions (Kinetic→Noetic) and ROS 2 (Foxy→Jazzy). > 50 video tutorials hosted by Labbé himself.

Documentation
Type & Roles
Software types
SLAM Library
Perception Stack

A Perception Stack encompasses the software layers that process data from cameras, LiDARs, IMUs, microphones, and other sensors in order to recognise the surrounding environment, perform localisation, detect and track objects, and interpret the scene. It is typically the first processing stage in an autonomous robot's data pipeline, feeding its outputs to planning and control stacks.

API Library

An API Library is a software package that exposes programmatic interfaces for communicating with a device, service, or system. In robotics it typically forms a lightweight integration layer built on top of the manufacturer's official API or an open-source project, abstracting low-level protocol details and providing language-native bindings (Python, C++, Java, etc.).

Select an item to see its description.
Main category
Perception & Vision SoftwareSDKs
Roles in robotics ecosystem
PerceptionComputer VisionSLAM & LocalizationAPI AccessDeveloper Enablement
Software family
Family
Perception & Vision

A family of open-source robotic perception libraries: Visual SLAM (ORB-SLAM, RTAB-Map), computer vision (OpenCV), point cloud processing (PCL, Open3D), detection and segmentation (YOLO, Detectron2).

Maturity & Adoption
9 / 9
Proven in operational conditions
ResearchPrototypeProduction
Adoption scaleIndustry Standard
Maintenance statusActively Maintained
First release2013
Last update20 May 2026
Deployments

Clearpath Husky/Jackal/Warthog (official integration), Boston Dynamics Spot (community), TurtleBot 2/3/4 (recommended SLAM), NASA JPL Mars analog rovers, IntRoLab humanoids. > 1500 citations in scientific papers on mapping and mobile autonomy.

Community

github.com/introlab/rtabmap ~3.0k★, github.com/introlab/rtabmap_ros ~1.0k★, > 50 official video tutorials on YouTube (Mathieu Labbé), 24/7 support at introlab.3it.usherbrooke.ca/mis/IntRoLab/RTAB-Map.

Organizations
Depends on
O
OpenCV
Open Source Computer Vision Library — the most widely used open-source computer vision library (> 4000 functions). Initiated in 1999 by Gary Bradski at Intel; today maintained by the OpenCV Foundation.
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P(
PCL (Point Cloud Library)
An open-source C++ library for processing 3D point clouds — filtering, segmentation, registration (ICP), 3D features, surface reconstruction. Initiated at Willow Garage in 2010.
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Integrates with
R2
ROS 2
Open-source framework for building robot software. The successor to ROS 1, built on DDS with native support for distributed, real-time and multi-platform systems. The de facto standard in research and commercial robotics.
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R2
ROS 2 Humble Hawksbill
LTS release of the ROS 2 framework based on Ubuntu 22.04, supported through May 2027. The most widely deployed release in humanoids, AMRs, and research platforms. Full integration with Nav2, MoveIt 2 and ros2_control.
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R2
ROS 2 Jazzy Jalisco
ROS 2 Jazzy Jalisco — the latest LTS (May 2024, supported until May 2029) on Ubuntu 24.04. C++17, Fast DDS 3.0, improved executors, RMW Zenoh, better QoS for variable networks.
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R
realsense-ros
The official Intel ROS 2 wrapper for RealSense cameras. Publishes depth, color, infrared, IMU, and pointcloud2 topics; supports an Action Server for calibration triggers. The IntelRealSense/realsense-ros repo — the most installed camera wrapper in ROS 2.
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O
OpenCV
Open Source Computer Vision Library — the most widely used open-source computer vision library (> 4000 functions). Initiated in 1999 by Gary Bradski at Intel; today maintained by the OpenCV Foundation.
→
P(
PCL (Point Cloud Library)
An open-source C++ library for processing 3D point clouds — filtering, segmentation, registration (ICP), 3D features, surface reconstruction. Initiated at Willow Garage in 2010.
→
N
Nav2
The professionally-supported successor to the ROS Navigation Stack — a production-grade navigation framework for mobile robots, quadrupeds, and AGVs. Behavior Trees, planners (Smac, NavFn, Theta*), controllers (MPPI, RPP, DWB), AMCL, costmaps.
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M2
MoveIt 2
Open-source motion planning, manipulation, and kinematics framework for ROS 2 (Foxy → Jazzy). Stewarded by PickNik Robotics. The de facto standard for manipulators in the ROS ecosystem.
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Related robotics software
C
Cartographer
An open-source 2D / 3D pose-graph SLAM library. Created at Google in 2016 (Wolfgang Hess et al.). Supports 2D and 3D LiDAR with IMU integration and a cartographer_ros package for ROS / ROS 2.
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O
ORB-SLAM3
An open-source third-generation Visual SLAM framework from the University of Zaragoza. Supports monocular, stereo, and RGB-D cameras as well as Visual-Inertial SLAM. Version 1.0 was released in July 2021.
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K
KISS-ICP
KISS-ICP — simple, fast and accurate LiDAR odometry / ICP scan matcher from the University of Bonn (Stachniss Lab), designed under the 'keep it small and simple' motto for 3D scan-to-scan registration.
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O
OpenCV
Open Source Computer Vision Library — the most widely used open-source computer vision library (> 4000 functions). Initiated in 1999 by Gary Bradski at Intel; today maintained by the OpenCV Foundation.
→
P(
PCL (Point Cloud Library)
An open-source C++ library for processing 3D point clouds — filtering, segmentation, registration (ICP), 3D features, surface reconstruction. Initiated at Willow Garage in 2010.
→
R
realsense-ros
The official Intel ROS 2 wrapper for RealSense cameras. Publishes depth, color, infrared, IMU, and pointcloud2 topics; supports an Action Server for calibration triggers. The IntelRealSense/realsense-ros repo — the most installed camera wrapper in ROS 2.
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ROS supportCompatibility with ROS / ROS 2 ecosystem
Official ROS 2 PackagePakiet dostępny w oficjalnym rejestrze ROS 2 przez rosdep / apt (packages.ros.org)
Official ROS 1 PackagePakiet dostępny w oficjalnym rejestrze ROS 1 (packages.ros.org)
ROS 2 RVIZ2 PluginPlugin do narzędzia RViz2 (wizualizacja 3D dla ROS 2)
System capabilities
⊙
Open source
Source code is publicly available under an open-source license — enables security audits, custom modifications, and integration without licensing barriers.
✓
⚡
Real-time capable
Designed with timing-determinism guarantees — meets the requirements of control loops, safety systems, and tasks demanding low, predictable latency.
✓
⟨/⟩
API available
The software exposes a programmable interface (REST, gRPC, SDK, or language bindings) that enables automation and integration with other systems.
✓
📦
Pre-built / binary
Distributed as ready-to-use binary packages, container images, or installers — no need to build from source.
✓
Programming languages
C++Python
Operating systems
Ubuntu 22.04Ubuntu 20.04DebianmacOSWindows
Minimum hardware requirements
Minimum hardware requirements
CPUQuad-core x86-64 ≥ 2 GHz or ARM64 (Jetson Orin Nano+) — RTAB-Map is multi-threaded.
RAM (GB)4
GPUCUDA-compatible (NVIDIA GTX 1060+) recommended for GPU bag-of-words; also works CPU-only.
Disk (GB)5

Databases can grow to several GB for large maps. Ubuntu 22.04 + ROS 2 Humble/Jazzy recommended.

Packaging & distribution
Package managers
apt / debSource – CMake / ament_cmakeDocker / Docker HubGitHub Releases / GitHub Actions Artifactssnap (Snapcraft)
CPU architectures
x86_64 (AMD64)ARM64 / AArch64NVIDIA Jetson – AArch64 (JetPack)Apple Silicon – AArch64 (macOS)
Installation difficulty
LevelModerate
Protocols and interfaces
Communication protocols
ROS 2 TopicsROS 2 ServicesDDS (Data Distribution Service)Shared Memory (POSIX / mmap)
Hardware interfaces
Ethernet 1000BASE-T (Gigabit Ethernet)USB 3.0 / 3.1 Gen 1MIPI CSI-2
Latency classes
Soft Real-Time (20–100 ms)Soft Real-Time (100–500 ms)
Deployment types
Local WorkstationOn RobotEdgeContainerized
Supported simulators
Gazebo Harmonic
Gazebo Classic (Gazebo 11)
NVIDIA Isaac Sim
Official Docker images
ros:humble-desktopros:jazzy-desktop
Licenses
BSD-3-ClauseBSD 3-Clause Licensev3-Clause

License family: Permissive

ModificationDistributionCommercial useSublicensingPrivate useROS-compatibleOSI approvedFSF Free/LibreRequires attribution
Official text ↗SPDX ↗OSI ↗
Version history
RTAB-Map 0.22Dec 2024

Update for ROS 2 Jazzy, improved visual loop closure (DBoW3).

RTAB-Map 0.21Jun 2023

Full ROS 2 Humble + Iron support, fluid memory.

RTAB-Map 0.20.16Feb 2021

ROS 2 Foxy support, OctoMap integration added.

RTAB-Map 0.19Sept 2019

3D LiDAR support (Velodyne, Ouster), ICP odometry.

RTAB-Map 0.11Jun 2016

Full support for ROS Indigo/Kinetic, RGB-D + Stereo + LiDAR.

RTAB-Map 0.5Sept 2013

First public release from Labbé's PhD thesis.