Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloDevice-free human sensing and localization in collaborative human-robot workspaces: a case study
Anno di pubblicazione2016
FormatoElettronico
Autore/iStefano Savazzi, Vittorio Rampa, Federico Vicentini, Matteo Giussani
Affiliazioni autoriCNR-IEIIT CNR-IEIIT CNR-ITIA CNR-ITIA
Autori CNR e affiliazioni
  • FEDERICO VICENTINI
  • STEFANO SAVAZZI
  • VITTORIO RAMPA
Lingua/e
  • inglese
AbstractModern robot manufacturing is fostering the implementation of hybrid production systems characterized by human-robot cooperative tasks. Safety technologies for workers protection require advanced sensing capabilities and flexible solutions that are able to monitor the movements of the operator in proximity of moving robots. This paper proposes the use of wireless device-free localization (DFL) methods and architectures to detect and track a human worker in a cooperative human-robot industrial workspace. The DFL system is composed of groups of massively-interacting small, low-cost, embedded radio-frequency transceivers that perform received power measurements. These devices are anchored in fixed peripheral locations of the plant and provide localization of the worker, who peculiarly carries neither wireless active devices (device-free) nor specific tracking sensors (sensor-free sensing). Operator motion is, in fact, estimated by tracking the perturbations of the radio field induced by the human body, considering the effect of concurrently moving robot as non-stationary interference. The proposed localization and detection algorithm is based on the Jump Linear Markovian System - Interactive Multiple Model method and its positioning accuracy has been validated by experiments performed inside a robotic cell of an industrial test plant. The proposed DFL system has been implemented by employing IEEE 802.15.4 radio-frequency devices operating at 2.4 GHz and integrated into a software safety architecture. Finally, a software toolset has been designed to predict DFL accuracy, to verify experimental measurements and also to support the integration with pre-installed industrial sensors to increase the accuracy of the augmented system.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da1253
Pagine a1264
Pagine totali11
RivistaIEEE sensors journal
Attiva dal 2001
Editore: IEEE Sensors Council, - New York, NY
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1530-437X
Titolo chiave: IEEE sensors journal
Titolo proprio: IEEE sensors journal.
Titolo abbreviato: IEEE sens. j.
Titoli alternativi:
  • Sensors journal
  • Institute of Electrical and Electronics Engineers sensors journal
Numero volume della rivista16
Fascicolo della rivista5
DOI10.1109/JSEN.2015.2500121
Verificato da refereeSì: Internazionale
Stato della pubblicazionePreprint
Indicizzazione (in banche dati controllate)-
Parole chiaveHidden Markov models;Radio frequency;Robot kinematics;Robot sensing systems;Service robots
Link (URL, URI)http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7327134
Titolo parallelo-
Data di accettazione01/09/2015
Note/Altre informazioni-
Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
  • ITIA — Istituto di tecnologie industriali e automazione
Moduli CNR
  • ICT.P07.005.001 : Reti wireless integrate per accesso ad alta velocita'
Progetti Europei-
Allegati

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Citazione bibliograficaSavazzi, S.; Rampa, V.; Vicentini, F.; Giussani, M., "Device-free human sensing and localization in collaborative human-robot workspaces: a case study," in Sensors Journal, IEEE , vol.PP, no.99, pp.1-1 doi: 10.1109/JSEN.2015.2500121