We have developed and demonstrated an intelligent auto-organizing aerial robotic sensor network system composed of cameras installed on UAVs and ground fixtures for urban surveillance using the decentralised control paradigm. The system can auto-organize to meet user requirements, changes to user requirements and when new UAVs or ground cameras are added or are lost due to failure. User designated targets can be automatically tracked and handed over from one camera to another, to ensure continuous tracking. The cameras can also self adjust their positions and pointing angles to cooperatively cover areas of interest completely. We have achieved this by designing a software architecture for managing multiple interacting algorithms online and in parallel, facilitating incremental software development and debugging. We have adapted algorithms to become computationally efficient and effective for real world use online and on-board the UAVs, and ensured that the integration of video analytics and tactical behaviours work in real world settings. We have also achieved near optimal, online close coordination of the UAVs and ground cameras. To the best of our knowledge, this is the first proof-of-concept of a fully integrated intelligent auto-organizing aerial robotic sensor network system of cameras installed on UAVs and ground fixtures for urban surveillance.

我们已经开发并演示了一种智能自动组织的空中机器人传感器网络系统，该系统由分散安装在无人机上的摄像机和地面固定装置组成，用于城市监控。该系统可以自动组织以满足用户需求，更改用户需求以及何时添加新的无人机或地面摄像头或由于故障而丢失。用户指定的目标可以自动跟踪并从一台摄像机移交给另一台摄像机，以确保连续跟踪。摄像机还可以自我调整其位置和指向角度，以完全协作地覆盖感兴趣的区域。我们通过设计一种用于在线和并行管理多种交互算法的软件体系结构来实现这一点，从而促进了增量软件的开发和调试。我们已经对算法进行了调整，以使其在在线和机载UAV的现实世界中可以高效使用，并确保视频分析和战术行为的集成可以在现实环境中使用。我们还实现了无人机和地面摄像机的近乎最佳的在线紧密协作。据我们所知，这是完全集成的智能自动组织空中机器人传感器网络系统的第一个概念验证，该系统由安装在无人机和地面固定装置上的摄像头组成，用于城市监控。