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ALF: An autonomous localization framework for self-localization in indoor environments

机译:ALF:室内环境中自定位的自主定位框架

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摘要

A lot of algorithms and applications can benefit from position information. GPS localization has become a standard for outdoor usage. But if a higher accuracy is needed or within GPS-denied areas providing this knowledge is still an open and nontrivial topic. Especially for unknown or dynamic environments. In this paper we propose a framework which is capable of autonomously exploring unknown environments in a fully decentralized way. It provides accurate and real-time localization support for customers. The usual very time intensive manual deployment and position assignment of reference nodes is avoided. Additional we show that the algorithm can detect and handle Non Line of Sight (NLOS) issues which is a very important criteria for real world applications.
机译:许多算法和应用程序可以受益于位置信息。 GPS定位已成为户外使用的标准。 但如果需要更高的准确性或在提供这种知识的GPS拒绝区域内仍然是一个开放和不动性的话题。 特别是对于未知或动态环境。 在本文中,我们提出了一种框架,能够以完全分散的方式自主探索未知环境。 它为客户提供了准确和实时的本地化支持。 避免了通常的非常时间的密集手动部署和参考节点的位置分配。 另外我们表明该算法可以检测和处理非视线(NLOS)问题,这是真实世界应用的重要标准。

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