| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10327025 | Robotics and Autonomous Systems | 2014 | 9 Pages |
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 range finder. 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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
C. Sánchez, A. Soriano, M. Vallés, E. Vendrell, A. Valera,