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

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.

SANCHEZ BELENGUER Carlos;  SORIANO Angel;  VALLES Marina;  VENDRELL VIDAL Eduardo;  VALLERA Angel; 

2014-06-13

ELSEVIER SCIENCE BV

JRC88641

0921-8890,   

http://www.sciencedirect.com/science/article/pii/S0921889014000128,    https://publications.jrc.ec.europa.eu/repository/handle/JRC88641,   

10.1016/j.robot.2014.01.009,