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Multi-UAV Cooperative Path Planning for Sensor Placement Using Cooperative Coevolving Genetic Strategy

机译:使用协作协同遗传策略的传感器安置的多无人机协作路径规划

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With the continuing increase in use of UAVs (Unmanned Aerial Vehicles) in various applications, much effort is directed towards creating fully autonomous UAV systems to handle tasks independently of human operators. One such task is the monitoring of an area, e.g. by deploying sensors in this area utilizing a system of multiple UAVs to autonomously create an efficient dynamic WSN (Wireless Sensor Network). The locations, order and which UAV to deal with deployment of individual sensors is a complex problem which in any real life problem is deemed to be hard to solve using brute force methods. A method is proposed for multi-UAV cooperative path planning by allocation of sensor placement tasks between UAVs, using a cooperative coevolving genetic algorithm as a basis for the solution to the described challenge. Algorithms have been implemented and preliminary tested in order to show proof of concept.
机译:随着在各种应用中对无人机(无人机)的使用的不断增加,人们致力于创建完全自主的无人机系统来独立于人类操作员来处理任务。这样的任务之一是对区域的监视,例如监视。通过使用多个UAV的系统在该区域中部署传感器来自主创建高效的动态WSN(无线传感器网络)。位置,顺序以及哪个UAV应对单个传感器的部署是一个复杂的问题,在任何现实生活中的问题都被认为很难用蛮力方法解决。提出了一种通过在无人机之间分配传感器放置任务,使用协同进化遗传算法作为解决上述挑战的基础的多无人机协同路径规划方法。为了展示概念证明,已经实施了算法并进行了初步测试。

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