Course
RTAB-Map in ROS 101 Python
Learn how to use the rtabmap_ros package for performing RGB-D SLAM
Course Overview
Description
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
TurtleBot2
Level
Intermediate
Duration
1h 30m
Prerequisites
This course is part of this learning path:
Robot Navigation
2 weeks
What projects will you be doing?
![[ROS Q&A] 168 - What are the differences between global and local costmap](https://www.theconstruct.ai/wp-content/uploads/2020/05/demo_rtab.png "demo_rtab")
3D Mapping
Create a 3D representation of an environment
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.
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What’s next
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