Guo Kexin, Li Xiuxian, Xie Lihua
IEEE Trans Cybern. 2020 Jun;50(6):2590-2603. doi: 10.1109/TCYB.2019.2905570. Epub 2019 Apr 2.
This puts forth an infrastructure-free cooperative relative localization (RL) for unmanned aerial vehicles (UAVs) in global positioning system (GPS)-denied environments. Instead of estimating relative coordinates with vision-based methods, an onboard ultra-wideband (UWB) ranging and communication (RCM) network is adopted to both sense the inter-UAV distance and exchange information for RL estimation in 2-D spaces. Without any external infrastructures prepositioned, each agent cooperatively performs a consensus-based fusion, which fuses the obtained direct and indirect RL estimates, to generate the relative positions to its neighbors in real time despite the fact that some UAVs may not have direct range measurements to their neighbors. The proposed RL estimation is then applied to formation control. Extensive simulations and real-world flight tests corroborate the merits of the developed RL algorithm.
本文提出了一种用于全球定位系统（GPS）受限环境中无人机（UAV）的无基础设施协作相对定位（RL）方法。该方法采用机载超宽带（UWB）测距与通信（RCM）网络来感知无人机之间的距离，并在二维空间中交换信息以进行RL估计，而不是使用基于视觉的方法来估计相对坐标。在没有预先部署任何外部基础设施的情况下，每个智能体通过协作执行基于共识的融合，将获得的直接和间接RL估计进行融合，以实时生成其与邻居的相对位置，尽管有些无人机可能无法对其邻居进行直接测距。然后将所提出的RL估计应用于编队控制。大量的仿真和实际飞行测试证实了所开发的RL算法的优点。
