ChehabiMed / mobile-robot-localization-ROS

Precise localization of a mobile robot by fusing wheel odometry and IMU data using the Unscented Kalman Filter (UKF) from the robot_localization package. This repository is a continuation of the Mobile-robot-simulation-ROS repository.

Mobile Robot localisation

This repository extends the Mobile-robot-simulation-ROS repository by implementing advanced localization techniques. Here, we fuse wheel odometry and IMU data using the UKF (Unscented Kalman Filter) provided by the robot_localization package to achieve more precise localization of our robot.

Yellow: the filtered trajectory. Red: the wheel odometry trajectory.

Overview

In this extension, we enhance the existing mobile robot simulation with:

• Wheel Odometry and IMU Data Fusion: Combining data from the wheel odometry and IMU using the UKF to improve localization accuracy.

• Improved Localization: Utilizing the robot_localization package to achieve more precise and reliable robot positioning.

Setup

To get started with this enhanced simulation, ensure you have the following prerequisites installed:

• ROS Noetic
• Gazebo
• Rviz
• robot_localization package

Clone this repository into your ROS workspace and build it:

cd ~
git clone https://github.com/ChehabiMed/mobile-robot-localization-ROS
cd ~/catkin_ws
catkin_make 
source devel/setup.bash

Running the Simulation

Launch the localization simulation environment:

roslaunch my_robot_localization start_filter.launch 

Future Enhancements

Future updates may include:

• Adding stereo camera plugin and extracting visual odometry to fuse with existing data.
• Building a map using stereo vision.
• Enhancing the robot's appearance with detailed 3D models.

Contributing

Contributions to this repository are welcome! If you have suggestions, improvements, or bug fixes, feel free to open an issue or submit a pull request.

License

This project is licensed under the BSD 2-Clause "Simplified" License. See the LICENSE file for details.