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Data-Foraging-Oriented Reconnaissance Based on Bio-Inspired Indirect Communication for Aerial Vehicles

机译:基于生物启发的飞行器间接数据侦察侦察

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In recent years, aerial vehicles have allowed exploring scenarios with harsh conditions. These can conduct reconnaissance tasks in areas that change periodically and have a high spatial and temporal resolution. The objective of a reconnaissance task is to survey an area and retrieve strategic information. The aerial vehicles, however, have inherent constraints in terms of energy and transmission range due to their mobility. Despite these constraints, the Data Foraging problem requires the aerial vehicles to exchange information about profitable data sources. In Data Foraging, establishing a single path is not viable because of dynamic conditions of the environment. Thus, reconnaissance must be focused on periodically searching profitable environmental data sources, as some animals perform foraging. In this work, a data-foraging-oriented reconnaissance algorithm based on bio-inspired indirect communication for aerial vehicles is presented. The approach establishes several paths that overlap to identify valuable data sources. Inspired by the stigmergy principle, the aerial vehicles indirectly communicate through artificial pheromones. The aerial vehicles traverse the environment using a heuristic algorithm that uses the artificial pheromones as feedback. The solution is formally defined and mathematically evaluated. In addition, we show the viability of the algorithm by simulations which have been tested through various statistical hypothesis.
机译:近年来,飞行器已允许在恶劣条件下探索场景。它们可以在周期性变化且具有高时空分辨率的区域中执行侦察任务。侦察任务的目的是调查区域并检索战略信息。然而,由于其机动性,飞行器在能量和传输范围方面具有固有的限制。尽管有这些限制,但数据搜寻问题仍要求飞行器交换有关可获利数据源的信息。在数据搜寻中,由于环境的动态条件,建立单个路径是不可行的。因此,随着一些动物觅食,侦查必须集中在定期搜索有利的环境数据源上。在这项工作中,提出了一种基于数据启发的,基于生物启发的飞行器间接通信侦察算法。该方法建立了一些重叠的路径以识别有价值的数据源。受散光能量原理的启发,飞行器通过人工信息素间接通信。飞机使用启发式算法遍历环境,该算法使用人工信息素作为反馈。该解决方案已正式定义并进行了数学评估。此外,我们通过各种统计假设对模拟进行了仿真,证明了该算法的可行性。

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