局部节点和边缘传感器辅助下网格上入侵者的最优自主追击

Sufal Chandra Swar, Suresh Manickam, D. Casbeer, K. Kalyanam, S. Darbha
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引用次数: 2

摘要

及时发现入侵者可以确保保护区内高价值资产的安全。这个问题在跨越国际边界时显得尤为重要,当地形多孔、崎岖和危险时,这个问题就变得具有挑战性。在大片土地上有效地防范入侵者是一项乏味的任务;目前,它主要由保安人员执行,自动检测系统处于被动辅助作用。本文讨论了另一种自主方法,即利用一辆或多辆无人驾驶车辆(UVs),在地面智能传感器的辅助下,检测和定位入侵者。为了促进自主紫外线操作,该地区配备了无人值守地面传感器(UGSs)和激光围栏。这些传感器一起为紫外线提供入侵者的时间戳位置信息(节点和边缘检测)。出于安全考虑,我们假设传感器没有联网(中心节点可能被禁用,导致整个系统瘫痪),因此,uv必须访问传感器附近以收集其中的信息。这使得问题具有挑战性,因为必须使用局部和可能延迟的信息。我们通过考虑二维网格的面积和UV的单位速度来离散时间和空间,即从一个节点到相邻节点需要一个时间单位。入侵者速度较慢,需要两步时间才能完成相同的动作。我们计算最小-最大最优,即在最坏情况下捕获入侵者的最小步数,对于网格中不同的行数和列数以及一个和两个追捕者。
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Optimal Autonomous Pursuit of an Intruder on a Grid Aided by Local Node and Edge Sensors
Timely detection of intruders ensures the safety and security of high valued assets within a protected area. This problem takes on particular significance across international borders and becomes challenging when the terrain is porous, rugged and treacherous in nature. Keeping an effective vigil against intruders on large tracts of land is a tedious task; currently, it is primarily performed by security personnel with automatic detection systems in passive supporting roles. This paper discusses an alternate autonomous approach by utilizing one or more Unmanned Vehicles (UVs), aided by smart sensors on the ground, to detect and localize an intruder. To facilitate autonomous UV operations, the region is equipped with Unattended Ground Sensors (UGSs) and laser fencing. Together, these sensors provide time-stamped location information (node and edge detection) of the intruder to a UV. For security reasons, we assume that the sensors are not networked (a central node can be disabled bringing the whole system down) and so, the UVs must visit the vicinity of the sensors to gather the information therein. This makes the problem challenging in that pursuit must be done with local and likely delayed information. We discretize time and space by considering a 2D grid for the area and unit speed for the UV, i.e. it takes one time unit to travel from one node to an adjacent node. The intruder is slower and takes two time steps to complete the same move. We compute the min–max optimal, i.e. minimum number of steps to capture the intruder under worst-case intruder actions, for different number of rows and columns in the grid and for both one and two pursuers.
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