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Optimizing Systems with Conflicting Objectives Competing for a Limited Resource- Resubmission
[Technical Report, Final Report]
ARIZONA STATE UNIVERSITY
Pagination or Media Count:
Decentralized and distributed autonomous sensing and control methods for networked sensor systems have many applications in surveillance, Internet of Things IoT, autonomous cars, and UAV swarms. These decentralized autonomy methods are especially challenging when the network connecting the sensors is time varying. Moreover, when the network is large with 10s or even 100s of sensors connected, decision making for sensor resource management e.g., decisions on sensor mobility - sensors mounted on UAVs becomes computationally intensive, in fact, the complexity is exponential in the decision space and the number of sensors. To address these challenges, we developed an optimization framework called COLRO to optimize the limited sensing resources in a time-varying networked sensor system for a target tracking applicationwhile minimizing the computational effort.
[A, Approved For Public Release]