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首页> 外文期刊>International Journal of Advanced Robotic Systems >Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots
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Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots

机译：无人机与无人机之间在伽马辐射热点高精度定位中的合作

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This article discusses the highly autonomous robotic search and localization of radiation sources in outdoor environments. The cooperation between a human operator, an unmanned aerial vehicle, and an unmanned ground vehicle is used to render the given mission highly effective, in accordance with the idea that the search for potential radiation sources should be fast, precise, and reliable. Each of the components assumes its own role in the mission; the unmanned aerial vehicle (in our case, a multirotor) is responsible for fast data acquisition to create an accurate orthophoto and terrain map of the zone of interest. Aerial imagery is georeferenced directly, using an onboard sensor system, and no ground markers are required. The unmanned aerial vehicle can also perform rough radiation measurement, if necessary. Since the map contains three-dimensional information about the environment, algorithms to compute the spatial gradient, which represents the rideability, can be designed. Based on the primary aerial map, the human operator defines the area of interest to be examined by the applied unmanned ground vehicle carrying highly sensitive gamma-radiation probe/probes. As the actual survey typically embodies the most time-consuming problem within the mission, major emphasis is put on optimizing the unmanned ground vehicle trajectory planning; however, the dual-probe (differential) approach to facilitate directional sensitivity also finds use in the given context. The unmanned ground vehicle path planning from the pre-mission position to the center of the area of interest is carried out in the automated mode, similarly to the previously mentioned steps. Although the human operator remains indispensable, most of the tasks are performed autonomously, thus substantially reducing the load on the operator to enable them to focus on other actions during the search mission. Although gamma radiation is used as the demonstrator, most of the proposed algorithms and tasks are applicable on a markedly wider basis, including, for example, chemical, biological, radiological, and nuclear missions and environmental measurement tasks.
机译：本文讨论了户外环境中辐射源的高度自主的机器人搜索和定位。根据对潜在辐射源的搜索应该快速，精确和可靠的想法，使用人类操作员，无人驾驶飞行器和无人驾驶地面飞行器之间的合作可以使给定任务高效执行。每个组成部分在任务中都扮演着自己的角色。无人飞行器（在本例中为多旋翼飞机）负责快速数据采集，以创建感兴趣区域的准确正射影像和地形图。使用机载传感器系统直接对航空影像进行地理参考，并且不需要地面标记。必要时，无人机也可以执行粗略的辐射测量。由于地图包含有关环境的三维信息，因此可以设计用于计算代表骑乘性的空间梯度的算法。基于主要的空中图，操作人员定义了要应用的，携带高灵敏度伽马辐射探测器/探针的无人地面车辆要检查的目标区域。由于实际调查通常体现出任务中最耗时的问题，因此重点主要放在优化无人地面车辆的轨迹规划上。但是，在给定背景下，也可以使用有助于定向灵敏度的双探头（差分）方法。与先前提到的步骤类似，以自动化模式执行从任务前位置到关注区域中心的无人地面车辆路径规划。尽管操作员仍然是必不可少的，但是大多数任务是自动执行的，因此可以大大减轻操作员的负担，从而使他们能够在搜索任务中专注于其他动作。尽管使用伽马辐射作为演示器，但大多数提议的算法和任务都可以在明显更广泛的基础上应用，包括例如化学，生物，放射和核任务以及环境测量任务。

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