基于模拟退火的无人机协同目标观测

Beulah Moses, L. Jain
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引用次数: 2

摘要

模拟退火(SA)被用于解决各种组合优化问题和局部搜索问题。本文研究了无人机群协同目标观测问题。我们提出了一种改进的SA算法来优化每架无人机的位置,以观察最大数量的目标。CTO是研究多智能体合作的一个很好的例子。通过对爬坡算法和改进SA算法的比较,发现改进SA算法在几乎所有目标速度、无人机传感器距离和各种群体规模下都具有优越性。
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Cooperative Target Observation of UAVs using Simulated Annealing
Simulated Annealing (SA) is used to solve various combinatorial optimisation problems and local search problems. This paper deals with Cooperative Target Observation (CTO) by groups of Unmanned Aerial Vehicles (UAV). We propose a Modified SA algorithm for optimising the position of each of the UAVs to observe the maximum number of targets. CTO is a very good example of study of multi agent cooperation. We compare with Hill Climbing algorithm and Modified SA algorithm and find that the Modified SA algorithm is superior for almost all target speeds, UAV sensor ranges and various group sizes.
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