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Distributed Robotic Sensor Networks: An Information Theoretic Approach

Julian, Brian J. and Angermann, Michael and Schwager, Mac and Rus, Daniela (2012) Distributed Robotic Sensor Networks: An Information Theoretic Approach. The International Journal of Robotics Research, 31 (10), pp. 1134-1154. SAGE Publications. DOI: 10.1177/0278364912452675 ISSN 0278-3649

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Abstract

In this paper we present an information-theoretic approach to distributively control multiple robots equipped with sensors to infer the state of an environment. The robots iteratively estimate the environment state using a sequential Bayesian filter, while continuously moving along the gradient of mutual information to maximize the informativeness of the observations provided by their sensors. The gradient-based controller is proven to be convergent between observations and, in its most general form, locally optimal. However, the computational complexity of the general form is shown to be intractable, and thus non-parametric methods are incorporated to allow the controller to scale with respect to the number of robots. For decentralized operation, both the sequential Bayesian filter and the gradient-based controller use a novel consensus-based algorithm to approximate the robots’ joint measurement probabilities, even when the network diameter, the maximum in/out degree, and the number of robots are unknown. The approach is validated in two separate hardware experiments each using five quadrotor flying robots, and scalability is emphasized in simulations using 100 robots.

Item URL in elib:https://elib.dlr.de/77146/
Document Type:Article
Title:Distributed Robotic Sensor Networks: An Information Theoretic Approach
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Julian, Brian J.MITUNSPECIFIED
Angermann, MichaelDLRUNSPECIFIED
Schwager, MacBoston UniversityUNSPECIFIED
Rus, DanielaMITUNSPECIFIED
Date:September 2012
Journal or Publication Title:The International Journal of Robotics Research
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:31
DOI :10.1177/0278364912452675
Page Range:pp. 1134-1154
Publisher:SAGE Publications
ISSN: 0278-3649
Status:Published
Keywords:robotic, sensor network, distributed, information theory
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - VABENE (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation > Communications Systems
Deposited By: Angermann, Dr.-Ing. Michael
Deposited On:19 Sep 2012 10:45
Last Modified:06 Sep 2019 15:30

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