Associative Search Network for RSSI-based Target Localization in Unknown Environments
Résumé
Received Signal Strength Indicator (RSSI) is commonly considered
and is very popular for target localization applications, since it
does not require extra-circuitry and is always available on current devices.
Unfortunately, target localizations based on RSSI are aected with
many issues, above all in indoor environments. In this paper, we focus on
the pervasive localization of target objects in an unknown environment.
In order to accomplish the localization task, we implement an Associative
Search Network (ASN) on the robots and we deploy a real test-bed
to evaluate the eectiveness of the ASN for target localization. The ASN
is based on the computation of weights, to "dictate" the correct direction
of movement, closer to the target. Results show that RSSI through an
ASN is eective to localize a target, since there is an implicit mechanism
of correction, deriving from the learning approach implemented in the
ASN.
Origine : Fichiers produits par l'(les) auteur(s)
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