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UAVs vs. Pirates
ACM Transactions on Autonomous and Adaptive Systems ( IF 2.2 ) Pub Date : 2020-07-07 , DOI: 10.1145/3380782
Ruiwen Zhang 1 , Tom Holvoet 2 , Bifeng Song 1 , Yang Pei 1
Affiliation  

For the rising hazard of pirate attacks, unmanned aerial vehicle (UAV) swarm monitoring is a promising countermeasure. Previous monitoring methods have deficiencies in either adaptivity to dynamic events or simple but effective path coordination mechanisms, and they are inapplicable to the large-area, low-target-density, and long-duration persistent counter-piracy monitoring. This article proposes a self-organized UAV swarm counter-piracy monitoring method. Based on the pheromone map, this method is characterized by (1) a reservation mechanism for anticipatory path coordination and (2) a ship-adaptive mechanism for adapting to merchant ship distributions. A heuristic depth-first branch and bound search algorithm is designed for solving individual path planning. Simulation experiments are conducted to study the optimal number of plan steps and adaptivity scaling factor for different numbers of UAVs. Results show that merely decreasing revisit intervals cannot effectively reduce pirate attacks. Without the ship-adaptive mechanism, the proposed method reduces up to 87.2%, 43.2%, and 5.5% of revisit intervals compared to the Lèvy Walk method, the sweep method, and the baseline self-organized method, respectively, but cannot reduce pirate attacks; while with the ship-adaptive mechanism, the proposed method can reduce pirate attacks by up to 6.7% compared to the best of the baseline methods.

中文翻译:

无人机与海盗

对于不断上升的海盗袭击危险,无人机(UAV)群监测是一种很有前途的对策。以往的监测方法无论是对动态事件的适应性还是简单有效的路径协调机制都存在不足,不适用于大面积、低目标密度、长时间持续的反海盗监测。本文提出了一种自组织无人机群反海盗监测方法。基于信息素图,该方法的特点是(1)用于预期路径协调的预留机制和(2)用于适应商船分布的船舶自适应机制。启发式深度优先分支定界搜索算法被设计用于解决个体路径规划。进行仿真实验以研究不同数量无人机的最佳计划步骤数和自适应比例因子。结果表明,仅仅减少重访间隔并不能有效减少盗版攻击。在没有船舶自适应机制的情况下,与 Lèvy Walk 方法、sweep 方法和基线自组织方法相比,所提出的方法分别减少了高达 87.2%、43.2% 和 5.5% 的重访间隔,但不能减少海盗攻击;而通过船舶自适应机制,与最好的基线方法相比,所提出的方法可以减少高达 6.7% 的海盗攻击。与 Lèvy Walk 方法、sweep 方法和基线自组织方法相比,重访间隔分别为 2%、43.2% 和 5.5%,但不能减少海盗攻击;而通过船舶自适应机制,与最好的基线方法相比,所提出的方法可以减少高达 6.7% 的海盗攻击。与 Lèvy Walk 方法、sweep 方法和基线自组织方法相比,重访间隔分别为 2%、43.2% 和 5.5%,但不能减少海盗攻击;而通过船舶自适应机制,与最好的基线方法相比,所提出的方法可以减少高达 6.7% 的海盗攻击。
更新日期:2020-07-07
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