Large-scale Localization

TALLA: UWB localization with no boundaries

We introduced the TALLA system (TDoA Localization for Large-scale Areas) based on TDoA techniques. The TALLA user, equipped with a tag, is tracked through areas of arbitrary width, unlike the state of the art in which localization takes place in a specific “cell” delimited by anchors. In TALLA, these are not necessarily in range with respect to each other; their temporal synchronization takes place in multi-hop using a protocol that guarantees positioning accuracy equal to traditional systems. The work received the “best paper award” at IPIN’19, a reference conference for the localization community.
TALLA was used within more complex systems. First in logistics, implemented in the EIT D-TWIN project. In addition, TALLA was used for the collection of visitor trajectories at the MUSE in Trento, enabling research on mobility patterns in collaboration with UNIMI.

Large-scale deployments with anchor self-localization

One of the greater issues affecting infrastructure-based systems (including TALLA) is the deployment of anchors and the accurate acquisition of their coordinates. A system was developed (and validated in CLOVES) for the automatic determination of the position of the anchors (self-localization) in large areas.

Related publications

TALLA: Large-scale TDoA Localization with Ultra-wideband Radios
D. Vecchia, P. Corbalán, T. Istomin, G.P. Picco. International Conference on Indoor Positioning and Indoor Navigation (IPIN), 30 September 30 - October 3, 2019, Pisa, Italy. https://doi.org/10.1109/IPIN.2019.8911790
Best Paper Award
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Self-Localization of Ultra-Wideband Anchors: From Theory to Practice
P. Corbalán, G.P. Picco, M. Coors, V. Jain. In IEEE Access, vol. 11, March 2023. https://doi.org/10.1109/ACCESS.2023.3261567
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Poster abstract: Cloves: A Large-scale Ultra-wideband Testbed
D. Molteni, G.P. Picco, M. Trobinger, D. Vecchia. ACM Conference on Embedded Networked Sensor Systems (SenSys), Boston (USA), November 6-9, 2022. https://doi.org/10.1145/3560905.3568072
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