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Searching the diffusive source in an unknown obstructed environment by cognitive strategies with forbidden areas

机译：通过禁止地区的认知策略在未知阻碍环境中搜索扩散源

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摘要

Using sensing robots (searchers) to search for the diffusive source in indoor environments is a common and vital task in human society. Such environments, however, are always obstructed by some obstacles, and sometimes the prior information of obstacles is unknown. To solve the source searching problem in the random obstructed environment, this paper formalizes a general model (i.e. the structured map), in which random obstacles are denoted by obstructed cells. Then, we employ cognitive strategies to guide the searcher to perform the search, which are only employed in the environment without obstacles before. To prevent the searcher from being trapped by obstacles, we devise a passive escaping mechanism that marks some explored areas as forbidden areas. Once an area is marked, it cannot be reached by the searcher anymore. Two up-to-date cognitive strategies, i.e. Infotaxis and Entrotaxis are combined with the proposed mechanism to form the hybrid strategies: IWFA (Infotaxis with forbidden areas) and EWFA (Entrotaxis with forbidden areas). Each of them has four variants. The experimental results reveal the superiority of the hybrid strategies: IWFA-II and EWFA-II (two variants) achieve an improvement by a maximum of 28% and 27% in success rate, respectively, compared to their original strategies. The effectiveness of the hybrid strategies is also verified in the obstructed environment generated by the computational fluid dynamics (CFD) software, FLUENT, which considers the effect of obstacles on the diffusion of leaked substances. These findings show important practicality in our proposed hybrid strategies for actual search missions.
机译：使用传感机器人（搜索者）来搜索室内环境中的扩散源是人类社会中的共同点和重要的任务。然而，这种环境总是被一些障碍妨碍，有时障碍物的先前信息是未知的。为了解决随机障碍环境中的源搜索问题，本文正式地形成了一般模型（即结构化地图），其中随机障碍物由阻塞的细胞表示。然后，我们采用认知策略来指导搜索者执行搜索，这些搜索只在环境中使用的搜索没有障碍。为了防止搜索者被障碍物捕获，我们设计了一种被动逃脱机制，标志着一些探索的区域是禁区。一旦标记区域，搜索者就无法达到。两个最新的认知策略，即InfoTaxis和Entrotaxis与拟议的机制相结合，以形成混合策略：IWFA（InfoTaxis与禁区）和EWFA（禁止区域的Entbotaxis）。每个人都有四种变体。实验结果揭示了混合策略的优越性：IWFA-II和EWFA-II（两种变体）分别在其原始策略相比，成功率分别达到了最高28％和27％的成功率。杂交策略的有效性也在计算流体动力学（CFD）软件，流畅的障碍环境中验证，这考虑了障碍物对泄漏物质扩散的影响。这些调查结果表明我们提出的实际搜索任务的混合策略中的重要实用性。

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  • 来源
    《Building and Environment》 |2020年第12期|107349.1-107349.12|共12页
  • 作者

    Zhao Yong; Chen Bin; Zhu Zhengqiu; Chen Feiran; Wang Yiduo; Ji Yatai;

  • 作者单位

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China;

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China;

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China|Univ Amsterdam Grp Multiscale Networked Syst MNS Syst & Networking Lab SNE Sci Pk 904 POB 94323 NL-1096 XH Amsterdam Netherlands;

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China;

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China;

    Natl Univ Def Technol Coll Syst Engn 109 Deya Rd Changsha Hunan Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Indoor source localization; Autonomous search; Obstructed environment; Cognitive strategy; Forbidden areas;

    机译：室内源本地化;自主搜索;受阻环境;认知策略;禁区;

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