In this paper, a new algorithm, called cluster matching, is introduced for multi-robot localization and orientation. This algorithm deals with the case in which each robot has the capability to estimate the relative orientation of those robots (called neighbors) that are within its transmission range. Furthermore, the environment is equipped with a distance IR sensor scanning the robots and estimating the absolute positions and orientations of a number of the team robots without knowing their IDs. The IDs of these robots are reconstructed by matching the orientation obtained by the distance IR sensor with the relative orientation measured with on-board sensors. The localization and orientation of robots not visible to the distance IR sensor are obtained by collecting the information coming from the on-board sensors and thus reconstructing a complete map of the team distribution. The accuracy in the estimation of the location of these robots is enhanced by introducing a new algorithm which relies on the localization of neighbor robots. Several simulation scenarios are implemented on tens of robots to show the performance of the introduced algorithm. A new algorithm for multi-robot localization and orientation is introduced.Clusters of nodes scanned by distance IR sensor to estimate their location and orientation.The location and orientation of invisible robots are computed by using location estimation algorithm.Several simulation scenarios are implemented to indicate the performance of suggested algorithm.

Multi-robot localization and orientation estimation using robotic cluster matching algorithm

FRASCA, MATTIA;FORTUNA, Luigi
2015

Abstract

In this paper, a new algorithm, called cluster matching, is introduced for multi-robot localization and orientation. This algorithm deals with the case in which each robot has the capability to estimate the relative orientation of those robots (called neighbors) that are within its transmission range. Furthermore, the environment is equipped with a distance IR sensor scanning the robots and estimating the absolute positions and orientations of a number of the team robots without knowing their IDs. The IDs of these robots are reconstructed by matching the orientation obtained by the distance IR sensor with the relative orientation measured with on-board sensors. The localization and orientation of robots not visible to the distance IR sensor are obtained by collecting the information coming from the on-board sensors and thus reconstructing a complete map of the team distribution. The accuracy in the estimation of the location of these robots is enhanced by introducing a new algorithm which relies on the localization of neighbor robots. Several simulation scenarios are implemented on tens of robots to show the performance of the introduced algorithm. A new algorithm for multi-robot localization and orientation is introduced.Clusters of nodes scanned by distance IR sensor to estimate their location and orientation.The location and orientation of invisible robots are computed by using location estimation algorithm.Several simulation scenarios are implemented to indicate the performance of suggested algorithm.
Localization, Unit disk graph, Cluster network, Multi robots
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/16682
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