Abstract
Uninhabited autonomous vehicles(UAVs) are an increasingly important part of battlefield environments, and may soon be common in civilian applications such as disaster relief, environmental monitoring and planetary exploration. Such vehicles may be airborne, land-based or aquatic, though the focus so far has been on airborne vehicles for military applications, and this is the focus of the research presented here. We consider a heterogeneous group of UAVs drawn from several distinct classes and engaged in a search and destroy mission over an extended battlefield. During the mission, the UAVs perform Search,Confirm, Attack andBattle Damage Assessment (BDA) tasks at various locations. The tasks are determined in real-time by the actions of all UAVs and their consequences (e.g.,sensor readings), so that the task dynamics are stochastic. The tasks must, therefore, be allocated to UAVs in real-time as they arise, while ensuring that appropriate vehicles are assigned to each task. Each class of UAVs has its own sensing and attack capabilities, so the need for appropriate assignment is paramount.
We present a simple cooperative approach to this problem, based on distributed assignment mediated by centralized mission status information. We also suggest methods for decentralizing the allocation process using a minimum disturbance approach termed МiDAS (Minimum Disturbance Allocation Strategy).
This work was supported by the AFRL/VA and AFOSR Collaborative Center of Control Science (Grant F33615–01–2–3154).
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© 2004 Kluwer Academic Publishers
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Jin, Y., Polycarpou, M.M., Minai, A.A. (2004). Cooperative Real-Time Task Allocation among Groups of UAVs. In: Butenko, S., Murphey, R., Pardalos, P.M. (eds) Recent Developments in Cooperative Control and Optimization. Cooperative Systems, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0219-3_12
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DOI: https://doi.org/10.1007/978-1-4613-0219-3_12
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