How to fuse odometry & IMU using the robot_localization package Open Class
What you will learn in this Open Class
One way to get better odometry from a robot is by fusing wheels odometry with IMU data. We are going to see an easy way to do that by using the robot_localization package, an amazing ROS package that allows mixing any sensor information into a more stable and exact localization data by using Kalman Filters.
Even if robot_localization allows to mix many sensor data, in this class we are going to concentrate on mixing odometry with IMU only.
We will use a simulation of the Summit XL robot. But also, we will test our algorithms in a real Summit XL robot that Robotnik company has sent to us for preparing the classes. Some selected attendants to the class will get access to the robot during the class in a remote way through the ROSDS platform, so you will connect with a real robot located in Barcelona from anywhere in the world.
Robots used in this class:
- Summit XL robot from Robotnik: https://www.robotnik.eu/mobile-robots/summit-xl/
Full online courses related to this topic:
- Fuse Sensor Data to Improve Localization: http://www.theconstructsim.com/construct-learn-develop-robots-using-ros/robotigniteacademy_learnros/ros-courses-library/ros-robot-localization-package/
- ROS Navigation in 5 Days: http://www.theconstructsim.com/construct-learn-develop-robots-using-ros/robotigniteacademy_learnros/ros-courses-library/ros-courses-ros-navigation-in-5-days/
- Master the Summit XL robot: http://www.theconstructsim.com/construct-learn-develop-robots-using-ros/robotigniteacademy_learnros/ros-courses-library/mastering-ros-summit-xl/