Simultaneous Localization and Mapping you own this product

prerequisites
intermediate Git • YAML • Basic ROS 2 • Linux basics (installing and building software, working with command-line tools, shell basics, working with multiple terminals) • Math (translations, rotations, coordinate systems, linear algebra) • robotics sensors (IMU, LiDAR, Encoders) • intermediate Python
skills learned
map with slam_toolbox • localization with slam_toolbox • SLAM in the bag
Mateusz Sadowski
1 week · 6-8 hours per week · INTERMEDIATE
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Look inside

Keep tabs on your robot. RoboPrototype, the company you work for, is preparing to demo its autonomous beverage delivery robot for investors in a food court next month. Your CEO has tasked you with setting up SLAM (Simultaneous Localization and Mapping) on the robot, making it possible to locate the robot at all times. Using the Slam Toolbox, you’ll equip the robot with the ability to create a map of its environment as well as pinpoint its location on the map. You’ll also get firsthand experience mapping on real data captured on a Turtlebot3 Burger, a widely used mobile robot platform.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Mat Sadowski

Mat Sadowski is a robotics consultant with eight years of experience in the industry. He has experience working with over thirty worldwide clients on such platforms as mobile robots, unmanned boats, industrial robots, and even lawnmowers. In his spare time, Mat is developing the robotics newsletter Weekly Robotics. You can get up to date on his work by following him on LinkedIn or by following his blog.

prerequisites

This liveProject is for programmers interested in learning to apply SLAM on a robotic system. To follow this liveProject you’ll need a computer running Ubuntu 22.04 capable of running Gazebo and be familiar with the following:

TOOLS
  • Git
  • YAML
  • ROS 2
TECHNIQUES
  • Linux basics (installation, working with command line tools, shell basics, and multiple terminals)
  • Math (translations, rotations, coordinate systems, linear algebra)
  • Probability theory
  • Robotics sensors (IMU, LiDAR, Encoders)

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