Algorithms for Robotic Intelligent Systems for Predicting Fire Hazardous Situations at an Early Stage

O. Emelyanova, S. Efimov, S. Jatsun
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Abstract

There is a problem of promptly obtaining sufficient information about the chemical situation in the workplace and the territories adjacent to it, necessary and sufficient for taking appropriate measures. A possible solution to this problem, capable of implementing effective and continuous control over the concentration of harmful substances in the air over the entire territory of industrial facilities and adjacent territories, is the creation of a system for monitoring extreme situations using unmanned aerial vehicles. This solution involves the installation of a portable multi-channel gas analyzer on one or more autonomous unmanned aerial vehicles (UAVs) that move in the monitoring zone, controlling the level of pollution at given points and transmitting information to the decision-making center. Purpose of the study: development of algorithms for searching for the source of atmospheric pollution by the concentration of toxic gas measured by an onboard gas analyzer installed on a mobile instrument platform. An algorithm has been developed to control the autonomous movement of a mobile instrument platform to a source of toxic gas, taking into account the change in concentration and the choice of the type of a given trajectory of movement, which makes it possible to track the change in the dynamics of the concentration of toxic gases in the vicinity of the object of observation.
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机器人智能系统早期火灾危险预测算法研究
有一个问题是要迅速取得关于工作场所及其邻近地区的化学品情况的充分资料,这些资料是采取适当措施所必需和充分的。这个问题的一个可能的解决办法是建立一个使用无人驾驶飞行器监测极端情况的系统,以便能够有效和持续地控制整个工业设施和邻近地区的空气中有害物质的浓度。该解决方案涉及在一架或多架自动无人驾驶飞行器(uav)上安装便携式多通道气体分析仪,这些飞行器在监测区域内移动,控制给定点的污染水平,并将信息传输到决策中心。研究目的:开发一种算法,通过安装在移动仪器平台上的车载气体分析仪测量的有毒气体浓度来搜索大气污染源。开发了一种算法来控制移动仪器平台对有毒气体源的自主运动,考虑到浓度的变化和给定运动轨迹类型的选择,从而可以跟踪观察对象附近有毒气体浓度的动态变化。
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