%0 Journal Article %T A MODIFIED SAMPLING METHOD FOR LOCALIZATION ACCURACY IMPROVEMENT OF MONTE CARLO LOCALIZATION %J The International Conference on Applied Mechanics and Mechanical Engineering %I Military Technical College %Z 2636-4352 %A Awad-Allah, M. A. %A Abdelaziz, M. A. %A Shahin, M. A. %A Tolbah, F. A. %D 2018 %\ 04/01/2018 %V 18 %N 18th International Conference on Applied Mechanics and Mechanical Engineering. %P 1-9 %! A MODIFIED SAMPLING METHOD FOR LOCALIZATION ACCURACY IMPROVEMENT OF MONTE CARLO LOCALIZATION %K Monte Carlo Localization, Mobile robots %K Position estimation %K Particle filters %R 10.21608/amme.2018.35021 %X ABSTRACTUnmanned vehicles are devices that can move around and perform tasks without anoperator onboard. Such features are essential in many applications. Localization is avery important task in any autonomous mobile robot; in order to reliably navigate, therobot must keep accurate track of where it is. In the past few years Monte CarloLocalization (MCL) has been one of the most successful and popular approaches tosolve the localization problem. MCL is a Bayesian algorithm based on particle filters.This paper is an attempt to increase the accuracy of localizing a mobile robot bymodifying the way of generating samples from the proposal distribution of the MCLalgorithm. Results show improvements in localization accuracy as compared to thebasic MCL algorithm. %U https://amme.journals.ekb.eg/article_35021_e1dabe7368b2debac661a8573b1a0a43.pdf