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Detection Model in Collaborative Multi-Robot Monte Carlo Localization.

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5 Author(s)
Barea, R. ; Dept. of Electron., Alcala Univ., Madrid ; Lopez, E. ; Bergasa, L.M. ; Alvarez, S.
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This paper presents an algorithm for collaborative mobile robot localization based on probabilistic methods (Monte Carlo localization) used in assistant robots. When a root detects another in the same environment, a probabilistic method is used to synchronize each robot's belief. As a result, the robots localize themselves faster and maintain higher accuracy. The technique has been implemented and tested using a virtual environment capable to simulate several robots and using two real mobile robots equipped with cameras and laser range-finders for detecting other robots. The result obtained in simulation and with real robots show improvements in localization speed and accuracy when compared to conventional single-robot localization

Published in:

Distributed Intelligent Systems: Collective Intelligence and Its Applications, 2006. DIS 2006. IEEE Workshop on

Date of Conference:

15-16 June 2006