@inproceedings{cb11884e8853426a961b8c2b425dcaca,
title = "Monte Carlo localization for mobile robot using adaptive particle merging and splitting technique",
abstract = "Monte Carlo localization (MCL) is a success application of particle filter (PF) to mobile robot localization. In this paper, an adaptive approach of MCL to increase the efficiency of filtering by adapting the sample size during the estimation process is described. The adaptive approach adopts an approximation technique of particle merging and splitting (PM&S) according to the spatial similarity of particles. In which, particles are merged by their weight based on the discrete partition of the running space of mobile robot. Using the PM&S technique, a Merge Monte Carlo localization (Merge-MCL) method is detailed. Simulation results illustrate that the approach is efficient.",
keywords = "Merging, Monte Carlo localization, Particle filter, Splitting",
author = "Tiancheng Li and Shudong Sun and Jun Duan",
year = "2010",
doi = "10.1109/ICINFA.2010.5512017",
language = "英语",
isbn = "9781424457021",
series = "2010 IEEE International Conference on Information and Automation, ICIA 2010",
pages = "1913--1918",
booktitle = "2010 IEEE International Conference on Information and Automation, ICIA 2010",
note = "2010 IEEE International Conference on Information and Automation, ICIA 2010 ; Conference date: 20-06-2010 Through 23-06-2010",
}