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.

An Intelligent Auto-Organizing Aerial Robotic Sensor Network System for Urban Surveillance

Martinel N.;Micheloni C.;Foresti G. L.;
2021-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1207231
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