This paper introduces a new approach to the problem of simultaneously localizing a team of micro aerial vehicles (MAV) equipped with inertial sensors able to monitor their motion and with exteroceptive sensors. The method estimates a delayed state containing the trajectories of all the MAVs. The estimation is based on an Extended Information Filter whose implementation is distributed over the team members. The paper introduces two contributions. The former is a trick which allows exploiting the information contained in the inertial sensor data in a distributed manner. The latter is the use of a projection filter which allows exploiting the information contained in the geometrical constraints which arise as soon as the MAV orientations are characterized by unitary quaternions. The performance of the proposed strategy is evaluated with synthetic data. In particular, the benefit of the previous two contributions is pointed out.

Distributed Information Filters for MAV Cooperative Localization / Cristofaro, Andrea; Renzaglia, Alessandro; Martinelli, Agostino. - 83:(2013), pp. 133-146. (Intervento presentato al convegno 10th International Symposium on Distributed Autonomous Robotic Systems, DARS 2010 tenutosi a Lausanne; Switzerland) [10.1007/978-3-642-32723-0_10].

Distributed Information Filters for MAV Cooperative Localization

Cristofaro Andrea
;
2013

Abstract

This paper introduces a new approach to the problem of simultaneously localizing a team of micro aerial vehicles (MAV) equipped with inertial sensors able to monitor their motion and with exteroceptive sensors. The method estimates a delayed state containing the trajectories of all the MAVs. The estimation is based on an Extended Information Filter whose implementation is distributed over the team members. The paper introduces two contributions. The former is a trick which allows exploiting the information contained in the inertial sensor data in a distributed manner. The latter is the use of a projection filter which allows exploiting the information contained in the geometrical constraints which arise as soon as the MAV orientations are characterized by unitary quaternions. The performance of the proposed strategy is evaluated with synthetic data. In particular, the benefit of the previous two contributions is pointed out.
2013
10th International Symposium on Distributed Autonomous Robotic Systems, DARS 2010
Robots; Extended Kalman filters; Cooperative localization
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Distributed Information Filters for MAV Cooperative Localization / Cristofaro, Andrea; Renzaglia, Alessandro; Martinelli, Agostino. - 83:(2013), pp. 133-146. (Intervento presentato al convegno 10th International Symposium on Distributed Autonomous Robotic Systems, DARS 2010 tenutosi a Lausanne; Switzerland) [10.1007/978-3-642-32723-0_10].
File allegati a questo prodotto
File Dimensione Formato  
Cristofaro_Distributed-information_2013.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 287.33 kB
Formato Adobe PDF
287.33 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1329781
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 13
  • ???jsp.display-item.citation.isi??? 6
social impact