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Large Sensors with Adaptive Shape Realised by Self-stabilised Compact Groups of Micro Aerial Vehicles

机译:具有自适应形状的大型传感器,通过自稳定的紧凑型微型空中车辆实现

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As examples of applications of such distributed sensor arrays let us discuss electromagnetic field (EMF) measurement and radiation mapping, which may result in localization of sources of radiation and EMF transmitters, for motivation in this paper. For the task of radiation mapping and sources of radiation detection, huge radiation detection sensors (often carried by a truck) have to be used to measure the intensity of radiation and also to detect direction of the emitted radiation particles nowadays. Besides the great weight and limited operability, the shape of these conventional sensors cannot be optimally adjusted to the actual situation mainly due to the large device dimensions. In the second application, large antennas need to be deployed to achieve required sensitivity of EMF field mapping and sources of transmission localization, where the size and shape of the antenna have to be optimized prior the mission with limited possibility of their alternation during its deployment. Using MAVs with available light-weight sensors in a distributed mode overcomes these drawbacks and enables to solve the mentioned tasks in an optimal way. Moreover, it enables new perspectives and approaches of analysing properties of the EMF and radiation fields, such as interference of multiple fields from multiple sources, attenuation in different environments, and reflections, in real-world scenarios, while now this research is limited to laboratory conditions. From the multi-MAV research perspective, this is a challenging example of using large groups of self-stabilized MAVs, whose shape is directly determined by the measured properties of the surrounding environment. It is one of the few examples, where the deployment of multi-MAV team is really necessary and which cannot be solved by a single platform only, as it is the case of most of the multi robot systems motivated only by reduction of overall time of the mission. The proposed approach differs from the available distributed sensor systems that enable to obtain sensory information in multiple locations. It goes beyond these systems by considering all measuring devices as a single distributed sensor in a similar way as static sensory arrays used for RFID (Radio Frequency Identification) localisation. See https://comtel.fel.cvut.cz/en/projects/rfid-locator for an example of such static array (a test of a similar technology, where each MAV of the group carries one of the small antennas of the sensor, is shown in Sect. 3).
机译:作为这种分布式传感器阵列的应用的示例,让我们讨论电磁场(EMF)测量和放射线映射,这可能导致辐射源和EMF发射器的定位,用于本文的动机。对于辐射映射的任务和辐射检测来源,必须使用巨大的辐射检测传感器(通常由卡车承载)来测量辐射的强度,也可以检测所发射的辐射颗粒的方向。除了重量和有限的可操作性之外,这些传统传感器的形状不能最佳地调整到实际情况,主要是由于大量的装置尺寸。在第二应用中,需要部署大天线以实现EMF场映射的所需灵敏度和传输定位的源,其中必须在其部署期间具有有限的可能性来优化天线的大小和形状。在分布式模式下使用带有可用的轻量级传感器的MAV克服了这些缺点,并使能以最佳方式解决提到的任务。此外,它能够实现新的透视和分析EMF和辐射场的特性的方法,例如来自多个领域的多个领域的干扰,在不同环境中的衰减,以及现实世界场景中的反射,而现在这项研究仅限于实验室状况。从多MAV研究的角度来看,这是使用大型自稳压MAV的具有挑战性的,其形状直接由周围环境的测量性质决定。它是少数个例子之一,其中多MAV团队的部署是真正必要的,并且只有单个平台无法解决,因为它是大多数多机器人系统的情况,只有通过减少总时间而产生的使命。所提出的方法与可用的分布式传感器系统不同,使能在多个位置处获得感官信息。通过将所有测量装置视为单个分布式传感器以与用于RFID(射频识别)定位的静态感觉阵列类似的方式,它超出了这些系统。有关此类静态阵列的示例,请参阅https://comtel.fel.cvut.cz/en/projects/rfid-locator(类似技术的测试,该组的每个MAV都带有传感器的一个小天线之一,被阐述。3)。

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