Zhang Ziyong, Xu Xiaoling, Cui Jinqiang, Meng Wei
The Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
Peng Cheng Laboratory, Shenzhen 518055, China.
Sensors (Basel). 2021 Mar 31;21(7):2400. doi: 10.3390/s21072400.
This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.
本文关注使用多架无人机（UAV）基于相对定位的最优区域覆盖布局。假设在执行区域覆盖任务之前只有一架无人机具有其全局位置信息，并且可以通过使用超宽带（UWB）传感器在无人机之间获得距离测量值。在这种情况下，多无人机相对定位和协同覆盖控制必须同时运行，这是一项极具挑战性的任务。在本文中，我们提出了一种基于单个地标点的相对定位算法，并结合了分布式覆盖控制律。同时，通过在最优相对定位和最优覆盖控制之间进行折衷，将最优多无人机布局问题表述为一个二次规划问题，并使用序列二次规划（SQP）算法进行求解。仿真结果表明，我们提出的方法能够保证一组无人机以协同方式有效地进行自我定位，同时完成区域覆盖任务。
