GEMA2: Geometrical Matching Analytical Algorithm for Fast Mobile Robots Global Self-Localization

Abstract: 

This paper presents a new algorithm for fast mobile robot self-localization in structured indoor environments based on geometrical and analytical matching, GEMA2. The proposed method takes advantage of the available structural information to perform a geometrical matching with the environment information provided by measurements collected by a laser rangefinder. In contrast to other global self-localization algorithms like Monte Carlo or SLAM, GEMA2 provides a linear cost with respect the number of measures collected, making it suitable for resource-constrained embedded systems. The proposed approach has been implemented and tested in a mobile robot with limited computational resources showing a fast converge from global self-localization.

Authors
Authors: 
VALLERA Angel, VENDRELL VIDAL Eduardo, SANCHEZ BELENGUER Carlos, SORIANO Angel, VALLES Marina
Publication Year
Publication Year: 
2014
Type

Type:

Appears in Collections
Appears in Collections: 
Institute for Transuranium Elements
Science Areas
Science Areas: 
JRC Institutes
ITU
Publisher
Publisher: 
ELSEVIER SCIENCE BV
ISSN
ISSN: 
0921-8890
Citation
Citation: 
ROBOTICS AND AUTONOMOUS SYSTEMS p. 855-863 no. 6 vol. 62