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Autonomous Mobile Sensor Placement in Complex Environments

Autonomous Mobile Sensor Placement in Complex Environments Autonomous Mobile Sensor Placement in Complex Environments NOVELLA BARTOLINI, TIZIANA CALAMONERI, and STEFANO CIAVARELLA, Sapienza University of Rome, Italy THOMAS LA PORTA, Pennsylvania State University, USA SIMONE SILVESTRI, Missouri University of Science and Technology, USA In this article, we address the problem of autonomously deploying mobile sensors in an unknown complex environment. In such a scenario, mobile sensors may encounter obstacles or environmental sources of noise, so that movement and sensing capabilities can be significantly altered and become anisotropic. Any reduction of device capabilities cannot be known prior to their actual deployment, nor can it be predicted. We propose a new algorithm for autonomous sensor movements and positioning, called DOMINO (DeplOyment of MobIle Networks with Obstacles). Unlike traditional approaches, DOMINO explicitly addresses these issues by realizing a grid-based deployment throughout the Area of Interest (AoI) and subsequently refining it to cover the target area more precisely in the regions where devices experience reduced sensing. We demonstrate the capability of DOMINO to entirely cover the AoI in a finite time. We also give bounds on the number of sensors necessary to cover an AoI with asperities. Simulations show that DOMINO provides a fast deployment with precise movements and no http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Autonomous and Adaptive Systems (TAAS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2017 by ACM Inc.
ISSN
1556-4665
DOI
10.1145/3050439
Publisher site
See Article on Publisher Site

Abstract

Autonomous Mobile Sensor Placement in Complex Environments NOVELLA BARTOLINI, TIZIANA CALAMONERI, and STEFANO CIAVARELLA, Sapienza University of Rome, Italy THOMAS LA PORTA, Pennsylvania State University, USA SIMONE SILVESTRI, Missouri University of Science and Technology, USA In this article, we address the problem of autonomously deploying mobile sensors in an unknown complex environment. In such a scenario, mobile sensors may encounter obstacles or environmental sources of noise, so that movement and sensing capabilities can be significantly altered and become anisotropic. Any reduction of device capabilities cannot be known prior to their actual deployment, nor can it be predicted. We propose a new algorithm for autonomous sensor movements and positioning, called DOMINO (DeplOyment of MobIle Networks with Obstacles). Unlike traditional approaches, DOMINO explicitly addresses these issues by realizing a grid-based deployment throughout the Area of Interest (AoI) and subsequently refining it to cover the target area more precisely in the regions where devices experience reduced sensing. We demonstrate the capability of DOMINO to entirely cover the AoI in a finite time. We also give bounds on the number of sensors necessary to cover an AoI with asperities. Simulations show that DOMINO provides a fast deployment with precise movements and no

Journal

ACM Transactions on Autonomous and Adaptive Systems (TAAS)Association for Computing Machinery

Published: May 29, 2017

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