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A Fluid Dynamic Based Coordination of a Wireless Sensor Network of Unmanned Aerial Vehicles: 3-D Simulation and Wireless Communication Characterization

机译:基于流体动力学的无人机无线传感器网络协调:3-D仿真和无线通信特性

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A fluid dynamic algorithm based on smoothed particle hydrodynamics (SPH) is proposed for coordination of a team of unmanned aerial vehicles (UAVs) in a wireless sensor network. SPH is a Lagrangian particle method typically used to model compressible and quasi-incompressible fluid flows. In this study, SPH is used to develop a decentralized controller for a swarm of fixed-wing UAVs, which move in 3-D space under constraints of airspeed and turning radius. Vector field path-following is used to guide the swarm towards the goal. We investigate circular, racetrack and counter-rotating loiter patterns for the UAVs in the goal region. This fluid dynamics coordination treatment allows UAVs to avoid collisions with obstacles and other flying UAVs. 3-D simulations are used to test the SPH-based control algorithm. Simulations were used to explore special cases, such as the modeling of obstacles with virtual SPH particles, and the use of a variable kernel to control the inter-vehicle separation. Finally, an aerial mobile sensor network is set up using SPH as the control mechanism, and an experimental characterization of air-to-air and air-to-ground communications is conducted. The experiments use two ground stations and three Delta-wing UAVs with a wingspan of 32 inches as nodes. Each node has a IEEE 802.15.4 ZigBee radio operating in the 2.4 GHz band. The low computational costs involved in the distributed SPH-based control algorithm make it an attractive option for implementation on simple inexpensive microprocessors. The results of simulations and experiments demonstrate the viability of setting up a mobile sensor network of inexpensive UAVs based on SPH.
机译:提出了一种基于平滑粒子流体动力学(SPH)的流体动力学算法,用于协调无线传感器网络中的无人飞行器(UAV)团队。 SPH是一种拉格朗日粒子方法,通常用于建模可压缩和准不可压缩的流体流。在这项研究中,SPH用于为一群固定翼无人机开发分散式控制器,这些无人机在空速和转弯半径的约束下在3-D空间中移动。矢量场路径跟踪用于引导群体朝向目标。我们研究了目标区域内无人机的圆形,跑道和反向旋转游荡模式。这种流体动力学协调处理使无人机能够避免与障碍物和其他飞行中的无人机相撞。 3-D仿真用于测试基于SPH的控制算法。仿真用于探索特殊情况,例如使用虚拟SPH粒子对障碍物进行建模,以及使用可变内核控制车辆之间的分离。最后,建立了以SPH为控制机制的空中移动传感器网络,并进行了空对空和空对地通信的实验表征。实验使用两个地面站和三个翼展为32英寸的Delta机翼无人机作为节点。每个节点都有一个工作在2.4 GHz频段的IEEE 802.15.4 ZigBee无线电。分布式基于SPH的控制算法所涉及的低计算成本使其成为在简单廉价的微处理器上实施的诱人选择。仿真和实验结果证明了建立基于SPH的廉价无人机的移动传感器网络的可行性。

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