Paper Info
Title
Distributed Cooperative Localization
Abstract
Localization for mobile platforms, in indoor scenarios, represents a cornerstone achievement to effective develop service and field robots able to safely cooperate. This paper proposes a methodology to achieve such a result by applying a completely decentralized and distributed algorithm. The key idea of the solution developed is to enable a dynamic correction of the position estimate, computed by robots, through information, shared during random rendezvous. This objective is reached using a specific extension of the Extended Kalman Filter, called Interlaced Extended Kalman Filter, which allows exchanging the estimation performed by any single robot together with the corresponding uncertainties. The proposed unsupervised method provides a large flexibility: it facilitates the handling of heterogeneous proprioceptive and exteroceptive sensors, that can be merged taking into account both their accuracy and the system model one. The solution is particularly interesting for rescue scenario, since it is able to cope with irregular communication signals and loss of connectivity among robots team without requiring any synchronization.
Year
DOI
Venue
2013
10.4018/jitr.2013070104
JITR
Keywords
Field
DocType
irregular communication signal,extended kalman filter,dynamic correction,field robot,exteroceptive sensor,corresponding uncertainty,heterogeneous proprioceptive,cornerstone achievement,indoor scenario,robots team,cooperative localization
Data mining,Extended Kalman filter,Synchronization,Computer science,Simulation,Distributed algorithm,Rendezvous,Robot,Simultaneous localization and mapping,System model,Mobile robot,Distributed computing
Journal
Volume
Issue
ISSN
6
3
1938-7857
Citations 
PageRank 
References 
1
0.43
19
Authors
4
Name
Order
Citations
PageRank
Stefano Panzieri126936.84
Federica Pascucci210615.62
Lorenzo Sciavicco312414.88
Roberto Setola445462.69