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Extended Kalman Filter SLAM from scratch on the Turtlebot3 with ROS2

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EKF SLAM From Scratch

In this project, I implmement an extended Kalman filter (EKF) simultaneous localization and mapping (SLAM) algorithm from scratch for the Turtlebot3 using C++ and ROS2. This includes a simulator so the algorithm can be tested in simulation before being tested on the real robot. A complete list of packages in this repository is provided in the next section

Package List

This repository consists of several ROS packages

  • nusim - A turtlebot simulation program using RVIZ
  • nuturtle_description - Defines the turtlebot's physical properties
  • nurtle_control - Recieves body twist commands and converts them to commands to move the robot
  • turtlelib
    • rigid2D: A 2D rigid body transformations library
    • diff_drive: A differential drive robot library
    • kalman: Extended Kalman Filter library
  • nuslam - Extended Kalman Filter SLAM for estimating the robot's pose and map based on sensor data
    • circle_fitting: Groups LIDAR data points into clusters, fits a circle to them, and classifies them

For a more detailed description of these packages, see the README files in each respective package.

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Extended Kalman Filter SLAM from scratch on the Turtlebot3 with ROS2

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