DocumentCode
2181267
Title
Solving ambiguities in MDS relative localization
Author
Di Franco, Carmelo ; Melani, Alessandra ; Marinoni, Mauro
Author_Institution
Scuola Superiore Sant´Anna, Pisa, Italy
fYear
2015
fDate
27-31 July 2015
Firstpage
230
Lastpage
236
Abstract
Monitoring teams of mobile nodes is becoming crucial in a growing number of activities. Where it is not possible to use fixed references or external measurements, one of the possible solutions involves deriving relative positions from local communication. Well-known techniques such as trilateration and multilateration exist to locate a single node although such methods are not designed to locate entire teams. The technique of Multidimensional Scaling (MDS), however, allow us to find the relative coordinates of entire teams starting from the knowledge of the inter-node distances. However, like every relative-localization technique, it suffers from geometrical ambiguities including rotation, translation, and flip. In this work, we address such ambiguities by exploiting the node velocities to correlate the relative maps at two consecutive instants. In particular, we introduce a new version of MDS, called enhanced Multidimensional Scaling (eMDS), which is able to handle these types of ambiguities. The effectiveness of our localization technique is then validated by a set of simulation experiments and our results are compared against existing approaches.
Keywords
Kalman filters; Mathematical model; Minimization; Noise measurement; Sensors; Standards; Stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Robotics (ICAR), 2015 International Conference on
Conference_Location
Istanbul, Turkey
Type
conf
DOI
10.1109/ICAR.2015.7251461
Filename
7251461
Link To Document