Robot localization in ROS
Published:
Paper
Monte Carlo Localization for Mobile Robots
Important: the project does not implement the paper, but uses the paper to answer some questions. Paper is just as a reference for better understanding.
About
In the project, we use Monte Carlo localization method, to detect the exact position of the robot in the 2 dimentional space. Map is known, and we have access to robot odometrzy and sensor data.
About Monte Carlo localization from Wikipedia:
Monte Carlo localization (MCL), also known as particle filter localization, is an algorithm for robots to localize using a particle filter. Given a map of the environment, the algorithm estimates the position and orientation of a robot as it moves and senses the environment.
Implementation
For the implementation we will use amcl ROS node, available as part of the navigation ROS stack.
If you want to know more about the ROS node, visit the official ROS node page.
Envorinment
To implemet and verify we use Gazebo. It is a free tool for robot simulation.
Code
All code is available on the Github