Abstract
This paper describes and compares two of the algorithms for indoor localization that are implemented in the localization add-on module for JADE. Described algorithms perform localization of agents running on smart devices in known indoor environments using only received WiFi signals from access points. First, distance estimates from access points are computed using received signal strength in routinary network discovery. Then, computed distance estimates are used to generate estimates of the position of the smart device that hosts the agent using one of described algorithms. The first algorithm, known as two-stage maximum-likelihood algorithm, is a well-known technique and it is considered a point of reference to evaluate the performance of other algorithms. The second algorithm, which has been recently introduced to overcome numerical-instability problems of classic geometric algorithms, works by turning localization into an optimization problem which is effectively solved using particle swarm optimization. In order to show the applicability of the proposed algorithms, the last part of the paper shows experimental results obtained in an illustrative indoor scenario, which is representative of envisioned applications.
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Monica, S., Bergenti, F. (2017). Indoor Localization of JADE Agents Without a Dedicated Infrastructure. In: Berndt, J., Petta, P., Unland, R. (eds) Multiagent System Technologies. MATES 2017. Lecture Notes in Computer Science(), vol 10413. Springer, Cham. https://doi.org/10.1007/978-3-319-64798-2_16
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