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ekfFusion is a ROS package designed for sensor fusion using Extended Kalman Filter (EKF). It integrates data from IMU, GPS, and odometry sources to estimate the pose (position and orientation) of a robot or a vehicle. This repository serves as a comprehensive solution for accurate localization and navigation in robotic applications.

• Sensor Fusion: Implements Extended Kalman Filter to fuse data from multiple sensors.
• Supported Sensors:
  • IMU (Inertial Measurement Unit)
  • GPS (Global Positioning System)
  • Odometry
• ROS Integration: Designed to work seamlessly within the Robot Operating System (ROS) environment.
• VectorNav Integration: Utilizes VectorNav package for IMU interfacing.
• UTM Conversion: Includes scripts for obtaining GPS data and transforming it into UTM (Universal Transverse Mercator) values.

• ROS (Robot Operating System) installed on your system. Follow the ROS installation instructions if you haven't already installed it.
• robot_localization ROS package.

Clone the repository into your ROS workspace and build it using catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/yourusername/ekfFusion.git
cd ..
catkin_make

1. Launch the ekfFusion node:

roslaunch ekfFusion ekf_fusion.launch

2. Subscribe to the fused pose topic to obtain the localization information.

• Configuration File: Adjust the sensor parameters and EKF settings in the configuration file located at ekfFusion/config/ekf_params.yaml.

Contributions are welcome! If you find any issues or want to suggest improvements, feel free to open an issue or submit a pull request.

This project is licensed under the MIT License - see the LICENSE file for details.

• Special thanks to the contributors of the robot_localization ROS package for providing a robust framework for sensor fusion.
• Credits to the developers of the VectorNav package for seamless IMU interfacing.