A novel resampling method for particle filter for mobile robot localization
Adiprawita W.a, Ahmad A.S.a, Sembiring J.a, Trilaksono B.R.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
Abstract
This paper present a particle filter for mobile robot localization also known as Monte Carlo Localization (MCL) to solve the localization problem of autonomous mobile robot. A new resampling mechanism is proposed. This new resampling mechanism enables the particle filter to converge quicker and more robust to kidnaping problem. This particle filter is simulated in MATLAB and also experimented physically using a simple autonomous mobile robot built with Lego Mindstorms NXT with 3 ultrasonic sonar and RWTH Mindstorms NXT Toolbox for MATLAB to connect the robot to MATLAB. The particle filter with the new resampling algorithm can perform very well in thesimulation as well as in physical experiments.
Author keywords
Indexed keywords
Autonomous mobile robot,LEGO mindstorm NXR,Monte carlo localization,Particle filter,Resampling,RWTH toolbox