@inproceedings{ff464fb2e8d74a118b229327a6ce98a2,
title = "Improved Monte Carlo Localization with robust orientation estimation for mobile robots",
abstract = "this paper proposes an improved Monte Carlo Localization algorithm with robust orientation estimation (IMCLROE) by incorporating an orientation estimate and weight calculation mechanism to determine an optimal orientation for particles and a tournament selection to reduce the number of particles for position tracking. Based on previously established sensory information, the proposed IMCLROE can improve the computational efficiency. Localization accuracy and localization failure rate are also significantly improved during position tracking while maintaining a minimal population of particles. Experimental results have confirmed the effectiveness of the proposed approach.",
keywords = "Monte Carlo Localization, Orientation estimation, Particle filter, Position tracking, Robot localization",
author = "Hsu, {Chen Chien} and Kuo, {Chia Jui} and Kao, {Wen Chung}",
year = "2013",
doi = "10.1109/SMC.2013.622",
language = "English",
isbn = "9780769551548",
series = "Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013",
pages = "3651--3656",
booktitle = "Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013",
note = "2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 ; Conference date: 13-10-2013 Through 16-10-2013",
}