Paper Info
Title
Differential Evolution To Enhance Localization Of Mobile Robots
Abstract
This paper focuses on the mobile robot localization problems: pose tracking, global localization and robot kidnap. Differential Evolution (DE) applied to extend Monte Carlo Localization (MCL) was investigated to better solve localization problem by increasing localization reliability and speed. In addition, a novel mechanism for effective robot kidnap detection was proposed. Experiments were performed using computer simulations based on the odometer data and laser range finder measurements collected in advance by a robot in real-life. Experimental results showed that integrating DE enables MCL to provide more accurate robot pose estimations in shorter time while using fewer particles.
Year
DOI
Venue
2011
10.1109/FUZZY.2011.6007721
IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011)
Keywords
Field
DocType
Monte Carlo Localization, Differential Evolution, particle filter, mobile robot
Motion planning,Computer vision,Computer science,Particle filter,Differential evolution,Pose,Artificial intelligence,Monte Carlo localization,Robot,Mobile robot,Machine learning,Odometer
Conference
ISSN
Citations 
PageRank 
1098-7584
6
0.42
References 
Authors
15
3
Name
Order
Citations
PageRank
Michal Lisowski160.76
Zhun Fan210613.81
Ole Ravn325654.31