With the flourishing development of Unmanned Aerial Vehicles (UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System (RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution. The result shows that the identified versions are consistent with the version change logs. Finally, it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.