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Optimizing the Control of a Group of Mobile Objects under Uncertainty
Optoelectronics, Instrumentation and Data Processing ( IF 0.5 ) Pub Date : 2020-01-01 , DOI: 10.3103/s8756699020010069
Ya. A. Mostovoy , V. A. Berdnikov

A swarm of moving objects coordinates the position of its individual objects in order to simultaneously solve a general problem set in a distributed manner. Planning the swarm operations comes across a problem of taking into account the possibility of operational regrouping of the swarm as the exact purpose of the swarm operation is not yet determined, or is a secret, or is set by a number of random circumstances. At the same time, the swam resources are not sufficient to simultaneously cover all possible targets in the operating region. Therefore, it is advisable to carry out the swarm operation in two phases and begin the first preliminary phase before resolving the mentioned uncertainties by creating a basic network with a relatively low concentration of swarm objects therein. In this case, one can significantly reduce the operation time. In the second phase of the operation, one locally simultaneously regroups the swarm objects, which takes a minimum time, to form a programmable percolation path that provides targeted coverage of the operating region. The solution to this problem is carried out by methods of the programmed percolation theory. The value of the swarm object concentration is obtained numerically using the results of statistical modeling of two-phase operations and analytically, thereby providing a minimum of total cost of the two-phase operation. The synergetics of information interaction of the swarm of objects in the implementation of a programmable percolation path is considered.

中文翻译:

不确定性下一组移动对象的优化控制

一群移动的对象协调其各个对象的位置,以便同时解决以分布式方式设置的一般问题。规划群操作遇到了一个问题,即考虑到群操作重组的可能性,因为群操作的确切目的尚未确定,或者是一个秘密,或者是由许多随机情况设定的。同时,游泳资源不足以同时覆盖作业区域内的所有可能目标。因此,建议在解决上述不确定性之前分两个阶段执行群体操作并开始第一个初步阶段,通过创建其中群体对象浓度相对较低的基本网络。在这种情况下,可以显着减少操作时间。在操作的第二阶段,在本地同时重新组合群对象,这需要最少的时间,以形成可编程的渗透路径,提供对操作区域的有针对性的覆盖。该问题的解决方案是通过程序化渗流理论的方法进行的。使用两阶段操作的统计建模结果和分析方法以数值方式获得群对象浓度的值,从而提供最小的两阶段操作总成本。考虑了在可编程渗透路径的实现中对象群的信息交互的协同作用。形成一个可编程的渗透路径,提供操作区域的目标覆盖。该问题的解决方案是通过程序化渗流理论的方法进行的。使用两阶段操作的统计建模结果和分析方法以数值方式获得群对象浓度的值,从而提供最小的两阶段操作总成本。考虑了在可编程渗透路径的实现中对象群的信息交互的协同作用。形成一个可编程的渗透路径,提供操作区域的目标覆盖。该问题的解决方案是通过程序化渗流理论的方法进行的。使用两阶段操作的统计建模结果和分析方法以数值方式获得群对象浓度的值,从而提供最小的两阶段操作总成本。考虑了在可编程渗透路径的实现中对象群的信息交互的协同作用。从而使两相操作的总成本最小。考虑了在可编程渗透路径的实现中对象群的信息交互的协同作用。从而使两相操作的总成本最小。考虑了在可编程渗透路径的实现中对象群的信息交互的协同作用。
更新日期:2020-01-01
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