Adaptive Formation Control of UAVs near Structures for Robust Localization and Efficient Task Execution

Accurate position estimation of unmanned aerial vehicles (UAVs) is essential for reliable and efficient task execution, such as the automated inspection of structures. However, localization is a significant challenge for UAVs in GNSS-denied spaces, such as under bridges, where satellite signals are obstructed. To address this issue, we employed a cooperative localization system consisting of a work-UAV, which performs tasks in the GNSS-denied space, and support-UAVs, which relatively localize the work-UAV. The critical challenge in this approach is the degradation of the GNSS-localization accuracy of the support-UAV owing to multipath effects, which are difficult to predict. This paper proposes an adaptive formation control method that enables support-UAVs to escape from multipath-affected spaces. Instead of focusing on signal processing or sensor fusion under multipath effects, our proposed system controls support-UAVs to escape from multipath-affected spaces where accurate GNSS-localization is difficult. This physical avoidance strategy enhances the robustness of the cooperative localization systems. Simulation results demonstrate the effectiveness of the proposed method. In two distinct scenarios, the average time spent by the support-UAV in multipath-affected spaces was reduced by 83.7% and 79.9%, respectively. Furthermore, the average task completion time was reduced by 37.6% and 14.3%, respectively.