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Autonomous Pest Bird Deterring for Agricultural Crops Using Teams of Unmanned Aerial Vehicles

机译:使用无人飞行器飞行队的农作物自主除虫鸟

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An algorithm for autonomous bird deterring using teams of unmanned aerial vehicles (UAVs) is being proposed in this paper. Birds cause significant damage to commercial crops globally. A bird deterring system using autonomous UAVs can potentially overcome the limitations of current bird management methods. The problem of controlling UAVs to deter birds is formulated as a model predictive control problem. Occupancy gird map is used to construct a world model which represents the system's knowledge of the current location of target birds. A bird behaviour model and a sensor model are derived based on experimental results from a series of field trials. The future state of the target is estimated by propagating the centralised world model in time. Cooperative deterring missions are planned autonomously by optimising cost functions assigned to each UAV. A series of simulated scenarios are used to demonstrate the effectiveness of the system at driving UAVs to protect an 8 hectare area from multiple bird flocks. Furthermore, it is demonstrated that by cooperating a team of two UAVs, the same bird deterring mission can be completed more efficiently compared to using a single UAV.
机译:本文提出了一种使用无人飞行器(UAV)团队进行自动鸟类阻吓的算法。鸟类对全球的商业作物造成了重大破坏。使用自主无人机的鸟类阻止系统可以克服当前鸟类管理方法的局限性。控制无人机以阻止鸟类的问题被表述为模型预测控制问题。占用区域图用于构建一个世界模型,该模型表示系统对目标鸟的当前位置的了解。基于一系列现场试验的实验结果,得出了鸟类行为模型和传感器模型。通过及时传播集中式世界模型来估计目标的未来状态。通过优化分配给每个无人机的成本函数,可以自主计划协作制止任务。使用一系列模拟场景来演示该系统在驾驶无人机保护8公顷区域免受多种禽类侵袭方面的有效性。此外,证明了通过与两个无人飞行器的团队合作,与使用单个无人飞行器相比,可以更有效地完成相同的鸟类扑灭任务。

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