复杂环境下的自主移动传感器安置

N. Bartolini, T. Calamoneri, S. Ciavarella, T. L. Porta, S. Silvestri
{"title":"复杂环境下的自主移动传感器安置","authors":"N. Bartolini, T. Calamoneri, S. Ciavarella, T. L. Porta, S. Silvestri","doi":"10.1145/3050439","DOIUrl":null,"url":null,"abstract":"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 oscillations, with moderate energy consumption. Furthermore, DOMINO provides better performance than previous solutions in all the operative settings.","PeriodicalId":377078,"journal":{"name":"ACM Transactions on Autonomous and Adaptive Systems (TAAS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Autonomous Mobile Sensor Placement in Complex Environments\",\"authors\":\"N. Bartolini, T. Calamoneri, S. Ciavarella, T. L. Porta, S. Silvestri\",\"doi\":\"10.1145/3050439\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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 oscillations, with moderate energy consumption. Furthermore, DOMINO provides better performance than previous solutions in all the operative settings.\",\"PeriodicalId\":377078,\"journal\":{\"name\":\"ACM Transactions on Autonomous and Adaptive Systems (TAAS)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Autonomous and Adaptive Systems (TAAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3050439\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Autonomous and Adaptive Systems (TAAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3050439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

在本文中,我们解决了在未知复杂环境中自主部署移动传感器的问题。在这种情况下,移动传感器可能会遇到障碍物或环境噪声源,因此运动和传感能力可能会发生重大变化,并成为各向异性。在实际部署之前,无法知道设备能力的任何减少,也无法预测。我们提出了一种新的自主传感器运动和定位算法,称为DOMINO(障碍物移动网络部署)。与传统方法不同,DOMINO通过在整个感兴趣区域(AoI)中实现基于网格的部署,并随后对其进行改进,以便在设备感知减少的区域中更精确地覆盖目标区域,从而明确地解决了这些问题。我们演示了DOMINO在有限时间内完全覆盖AoI的能力。我们还给出了覆盖带有凸起的AoI所需的传感器数量的界限。仿真结果表明,DOMINO部署速度快,运动精确,无振荡,能耗适中。此外,DOMINO在所有操作设置中提供了比以前的解决方案更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous Mobile Sensor Placement in Complex Environments
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 oscillations, with moderate energy consumption. Furthermore, DOMINO provides better performance than previous solutions in all the operative settings.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信