Distributed Localization of Heterogeneous Agents With Uncertain Relative Measurements and Communications

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Zamani, M (Author) Other; Aguiar, AP (Author) FEUP

Conference proceedings International

Title: Proceedings of the IEEE Conference on Decision and Control

Pages: 4702-4707

54th IEEE Conference on Decision and Control, CDC 2015

15 December 2015 through 18 December 2015

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00K-C06

DOI: 10.1109/cdc.2015.7402952

Abstract (EN): This paper presents a distributed filtering algorithm for networked agents modeled with independent linear state models and measurements. In addition to local state measurements, agents utilize relative state measurements and communicated state estimates to improve their individual state estimates. These kind of measurement models are motivated by the problem of localization in sensor networks and multi-vehicle robotics. In this paper, we explicitly consider that all the state models, measurements and communications are subject to disturbances and we propose a minimum-energy filtering approach to derive the state estimates. The filters are distributed due to the practical requirement that the agents are only allowed to exchange relative measurements and communications in their local neighbourhoods. Sufficient conditions guaranteeing the convergence of the proposed distributed algorithms are provided in terms of detectability conditions and also in terms of bounds on information sharing among the agents. A numerical example is provided that illustrates the performance of the proposed algorithm and also reinforces the importance of the convergence conditions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6