面向泛在机器人需求的模糊认知地图导航

J. Vaščák
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引用次数: 1

摘要

物联网(IoT)在过去五年中成为一种现象。有许多不同的应用,其潜力仍在增长。机器人技术也是物联网的前景领域之一,但它有一些特定的要求。所谓的智能空间(IS)的概念对于机器人应用特别方便,它可以从空间分布和相互联网的传感器中获益。首先,不需要携带所有必要的传感器,因此机器人变得更便宜,其次,这样的解决方案也可以更好地预测特定事件的发生。被称为Ubibot的无所不在机器人是物联网和is互连的问题。在本文中,我们提出了我们自己的Ubibot概念,其中用于导航目的的所谓的模糊认知地图(FCM)被使用。对于FCM参数的调整,采用了基于进化算法的自适应方法。对该系统进行了实验测试,并对实验结果进行了分析。
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Navigation Based on Fuzzy Cognitive Maps for Needs of Ubiquitous Robotics
Internet of Things (IoT) has become a phenomenon of last five years. There is a number of various applications and its potential is still growing. Robotics is also one of perspective areas for IoT but it has some specific requirements. The concept of the so-called intelligent space (IS) is especially convenient for robotic applications, which can profit from spatially distributed and mutually networked sensors. Firstly, it is not necessary to carry all necessary sensors on board and hereby robots become much cheaper and secondly, such a solution is able to better predict occurrence of specific events, too. A ubiquitous robot, known as Ubibot, is an issue of interconnecting of IoT and IS. In this paper we proposed our own concept of Ubibot, where for navigation purposes the so-called fuzzy cognitive map (FCM) was used. For adjusting FCM parameters our own adaptation method based on evolutionary algorithms was used. The proposed system was experimentally tested and obtained results were analysed.
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