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A fusion approach for the localization of humans in factory environments

机译:在工厂环境中将人本地化的融合方法

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Industrial automation increasingly relies on the automation and interconnection of formerly human operated transport machinery. Products are already moved by automated guided vehicles and machines like cranes may soon position themselves just in time based on context information. Human presence is however still required in some of these environments. This raises the question how to allow machines to sense a human's presence to enable context awareness functions and safety around autonomous machines. We propose a combination of Ultra-Wide Band (UWB) localization and Pedestrian Dead Reckoning (PDR) to achieve robust and reliable long- and short-term tracking of humans in an industrial environment. We highlight advantages and drawbacks of both localization methods, as well as current approaches to increase tracking accuracy of the individual technologies and their combination. Additionally, we present measurements using a Zero Velocity Update assisted PDR system and show that, under certain circumstances, the error of PDR can be reduced from 5% to 2% of the travelled distance. We also analyze the applicability of PDR correction methods in industrial environments. Our results show the potential of PDR for accurate short-term localization, supplanted by UWB to ensure long-term precision.
机译:工业自动化越来越依赖于以前的人工运输机械的自动化和互连。产品已经由自动引导车辆移动,起重机等机器可能很快会根据上下文信息及时定位自己。但是,在这些环境中的某些环境中,仍然需要人在场。这就提出了一个问题,即如何允许机器感知人类的存在,以实现上下文意识功能和自动机器周围的安全性。我们建议将超宽带(UWB)本地化和行人航位推算(PDR)结合起来,以在工业环境中实现对人类的长期和短期可靠而可靠的跟踪。我们着重介绍了两种定位方法的优缺点,以及当前提高单个技术及其组合的跟踪精度的方法。此外,我们提出了使用零速度更新辅助PDR系统进行的测量,结果表明,在某些情况下,PDR的误差可以从行进距离的5%减小到2%。我们还分析了PDR校正方法在工业环境中的适用性。我们的结果显示了PDR在准确的短期定位中的潜力,被UWB取代以确保长期的精度。

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