Simultaneous Localization and Mapping with Particle Swarm Localization

Author

Todor, B. ; Dárabos, Daiel

Author_Institution

Dept. Of Meas. & Inf. Syst, Budapest Univ. of Technol. & Econ., Budapest

fYear

2005

fDate

5-7 Sept. 2005

Firstpage

216

Lastpage

221

Abstract

In this article the authors present a simultaneous localization and mapping (SLAM) method based on probability distribution function matching. The algorithm randomly samples the posteriori pdf based on the reverse models of the range sensors, and then uses a simple function matching method to evaluate pose suggestions, which are proposed by a modified version of the particle swarm optimization method.

Keywords

SLAM (robots); mobile robots; particle swarm optimisation; path planning; random processes; statistical distributions; autonomous robot navigation; function matching; particle swarm localization; particle swarm optimization; probability distribution function matching; random sampling; range sensor; reverse models; simultaneous localization and mapping; Conferences; Data acquisition; Global Positioning System; Intelligent robots; Navigation; Orbital robotics; Particle swarm optimization; Robot sensing systems; Robotics and automation; Simultaneous localization and mapping; Particle swarm optimization; autonomous robot navigation; localization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2005. IDAACS 2005. IEEE

Conference_Location

Sofia

Print_ISBN

0-7803-9445-3

Electronic_ISBN

0-7803-9446-1

Type

conf

DOI

10.1109/IDAACS.2005.282973

Filename

4062124