PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs
Joint Authors
Grassi, Michele
Opromolla, Roberto
Savvaris, Al
Moccia, Antonio
Fasano, Giancarmine
Source
International Journal of Aerospace Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-04-04
Country of Publication
Egypt
No. of Pages
14
Abstract EN
This paper presents an original technique for robust detection of line features from range data, which is also the core element of an algorithm conceived for mapping 2D environments.
A new approach is also discussed to improve the accuracy of position and attitude estimates of the localization by feeding back angular information extracted from the detected edges in the updating map.
The innovative aspects of the line detection algorithm regard the proposed hierarchical clusterization method for segmentation.
Instead, line fitting is carried out by exploiting the Principal Component Analysis, unlike traditional techniques relying on least squares linear regression.
Numerical simulations are purposely conceived to compare these approaches for line fitting.
Results demonstrate the applicability of the proposed technique as it provides comparable performance in terms of computational load and accuracy compared to the least squares method.
Also, performance of the overall line detection architecture, as well as of the solutions proposed for line-based mapping and localization-aiding, is evaluated exploiting real range data acquired in indoor environments using an UTM-30LX-EW 2D LIDAR.
This paper lies in the framework of autonomous navigation of unmanned vehicles moving in complex 2D areas, for example, being unexplored, full of obstacles, GPS-challenging, or denied.
American Psychological Association (APA)
Opromolla, Roberto& Fasano, Giancarmine& Grassi, Michele& Savvaris, Al& Moccia, Antonio. 2017. PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs. International Journal of Aerospace Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1158031
Modern Language Association (MLA)
Opromolla, Roberto…[et al.]. PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs. International Journal of Aerospace Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1158031
American Medical Association (AMA)
Opromolla, Roberto& Fasano, Giancarmine& Grassi, Michele& Savvaris, Al& Moccia, Antonio. PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs. International Journal of Aerospace Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1158031
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1158031