Information fusion for USAR operations based on crowdsourcing
Information fusion for USAR operations based on crowdsourcing
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基于众包的美国搜救行动信息融合
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
M. Lewis
中科院分区：
文献类型：
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作者：
V. Zadorozhny;M. Lewis
在这篇文章中，我们介绍了用于城市搜救(USAR)行动的自动信息融合方法，该方法可以有效地“众包”受害者检测任务。我们减少了操作员的负担，要求他们只需在图像中确认受害者的存在(以注释图像)。通过自动融合来自图像队列的带注释的图像来执行寻找受害者位置的任务。这种多机器人信息融合是连续进行的；随着机器人集体探索更大的区域，估计的受害者坐标收敛到实际的受害者位置。
In this paper, we introduce automatic information fusion methods for the urban search and rescue (USAR) operations that efficiently “crowdsource” victim detection tasks. We reduce the load on the operators requiring them to acknowledge only presence of the victim in an image (to annotate the image). The task of finding victim location is performed via automatic fusion of annotated images from the image queue. This multi-robot information fusion is conducted continuously; as robots collectively explore larger areas, the estimated victim coordinates converge to actual victim locations.