模块化侦察机器人系统的区域侦察建模

Jan Nohel, P. Stodola, Jan Zezula, Pavel Zahradníček, Zdenek Flasar
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引用次数: 0

摘要

就在不同领域部署部队和资产而言,当代军事行动的开展可谓错综复杂。因此,从各种来源和传感器获得的信息是影响行动进程和结果的关键因素。在敌军后方或受到化学、生物、辐射和/或核(CBRN)等威胁的地区执行侦察任务时,必须具备稳健性、可变部署性、长期可持续性、模块化和灵活性。本文描述了指挥官对执行侦察任务的自主模块化机器人系统能力的要求,以支持他们的部队。它描述了在规划机器人系统操作时使用数学算法模型的可能性。战术决策支持系统模型的计算能力在对感兴趣区域进行侦察的两个方案中得到了验证。侦察任务不同部分的部分计算按逻辑顺序进行。实地测试实际验证了机器人系统执行侦察任务的变体。数字地形和浮雕模型、数学算法模型和变体模型的使用提高了规划和部署一组机器人系统对感兴趣区域进行侦察的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Area reconnaissance modeling of modular reconnaissance robotic systems
In terms of deploying forces and assets in different domains, the conduct of contemporary military operations can be characterized as complex. Information obtained from a wide range of sources and sensors is thus a crucial factor influencing the course and outcome of an operation. It must be robust, variably deployable, sustainable long-term, modular, and flexible when performing reconnaissance tasks in the rear of enemy forces or in areas threatened by, for example, chemical, biological, radiological, and/or nuclear (CBRN) threats. This paper describes the requirements of commanders for the capabilities of autonomous modular robotic systems performing reconnaissance tasks to support their units. It characterizes the possibilities of using mathematical-algorithmic models in planning the operation of robotic systems. The computational capabilities of tactical decision support system models are demonstrated on two scenarios for the reconnaissance of an area of interest. The partial calculations of the different parts of the reconnaissance task are performed in a logical sequence. Field tests practically verified the variants of performing reconnaissance tasks by robotic systems. The use of digital terrain and relief models, mathematical-algorithmic models, and variant modeling has increased the efficiency of the planning and deployment of a group of robotic systems in the reconnaissance of an area of interest.
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