Uniform clustered particle filtering for robot localization

Localization is a fundamental ability for an autonomous mobile robot. Different particle filter based solutions to the problem are simulated in a software simulator, and the results are compared and discussed. The weighted bootstrap alter, clustering particle alter, and the uniform particle alter are examined. A new method based on the clustered particle alter and the uniform particle alter the uniform clustering particle alter, is also proposed and evaluated.