RTAB-Map in ROS 101 Python

Learn how to use the rtabmap_ros package for performing RGB-D SLAM

Course Overview


RTAB-Map (Real-Time Appearance-Based Mapping) is an RGB-D SLAM approach based on a loop closure detector.

The loop closure detector uses a bag-of-words approach in order to determinate if a new image detected by an RGB-D sensor is from a new location or from a location that has been already visited.

Of course, this is a very summarized explanation. You will get more details on how this loop closure detector works inside this Course.

Learning Objectives

  • Learn the basics of RTAB-Map
  • Use the rtabmap_ros package
  • Understand how the loop closure detection works internally
  • Create a 3D Map of an environment
  • Autonomous Navigation using RGB-D SLAM.

Simulation robots used in this course






1h 30m

This course is part of this learning path:

What projects will you be doing?

[ROS Q&A] 168 - What are the differences between global and local costmap

3D Mapping

Create a 3D representation of an environment

ROS Mini Challenge #2 - RViz

Data Visualization (RViz)

Visualize the data that the robot simulation is providing

Autonomous Navigation using RGB-D SLAM

Perform Autonomous Navigation using the rtabmap_ros.

What you will learn

Course Syllabus

Unit 1: Introduction to the Course
  • What is RTAB-Map
  • Demo
  • What you will learn

10 min.

Unit 2: Basic Concepts
  • System Requirements
  • Data Visualization – RViz
  • Launching RTAB-Map
  • Subscribed Topics
  • Arguments

30 min.

Unit 3: Autonomous Navigation with rtabmap_ros
  • Mapping Mode
  • Localization Mode
  • Autonomous Navigation

40 min.

Unit 4: Final Recommendations

Keep Learning

10 min.

Ready to get started?

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What’s next

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