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Inflight Rerouting for an Unmanned Aerial Vehicle

机译:无人机航路改航

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摘要

The availability of new information can often necessitate rerouting of a vehicle. In [1], the set of nonoverlapping useful vicinities of the reconnaissance sites, S, and the 3D space over them was represented using a discrete graph-model. Here, we consider two cases in which an unmanned reconnaissance aerial vehicle must be rerouted. The first scenario involves not visiting useful vicinities, S_t is contained in S, due to newly reported unacceptable threat-levels in their neighborhood. In the second scenario, visitations to useful vicinities, S_t is contained in S, is made redundant due to decreased importance of the sites to which they offer a vantage observation-point. Our earlier graph-model is general enough to provide a basic framework for consideration of rerouting in both cases. We give an algorithm to obtain a graph-model, from the earlier one, that allows efficient gene encoding and efficient application of GA operators to obtain new alternative rerouting plans.
机译:新信息的可用性通常可能需要重新路由车辆。在[1]中,使用离散图模型表示了侦察站点S和它们上方的3D空间的非重叠有用区域集。在这里,我们考虑两种情况,其中无人侦察飞行器必须改道。第一种情况涉及不访问有用的区域,S_t包含在S中,这是由于新报告的附近威胁级别不可接受。在第二种情况下,由于有用的观察点所占位置的重要性降低,因此对访问附近有用的访问S_t包含在S中变得多余。我们之前的图模型足够通用,可以为两种情况下的重新路由提供一个基本框架。我们提供了一种从较早的模型中获取图模型的算法,该模型允许有效的基因编码和GA运算符的有效应用来获得新的替代路线规划。

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