论文标题
部分可观测时空混沌系统的无模型预测
Zero Touch Coordinated UAV Network Formation for 360° Views of a Moving Ground Target in Remote VR Applications
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Unmanned aerial vehicles (UAVs) with on-board cameras are widely used for remote surveillance and video capturing applications. In remote virtual reality (VR) applications, multiple UAVs can be used to capture different partially overlapping angles of the ground target, which can be stitched together to provide 360° views. This requires coordinated formation of UAVs that is adaptive to movements of the ground target. In this paper, we propose a joint UAV formation and tracking framework to capture 360° angles of the target. The proposed framework uses a zero touch approach for automated and adaptive reconfiguration of multiple UAVs in a coordinated manner without the need for human intervention. This is suited to both military and civilian applications. Simulation results demonstrate the convergence and configuration of the UAVs with arbitrary initial locations and orientations. The performance has been tested for various number of UAVs and different mobility patterns of the ground target.
