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/ | |||||||||||||||
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Document Type: | Article | |||||||||||||||
Title: | Distributed Robotic Sensor Networks: An Information Theoretic Approach | |||||||||||||||
Authors: |
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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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