ManagementAutonomous SystemsOptimizationSchedulingUnmanned Aircraft SystemsConstraint-based SchedulingDynamic SchedulingMulti-objective OptimizationMulti-objective SchedulingMultiobjective OptimizationTask AllocationContract Net ProtocolDynamic Multi-objective SchedulingDynamic Task SchedulingMulti-constraint OptimizationMulti-objective Resource-constrained SchedulingSingle-objective OptimizationWeighted Sum Scheduling
Unmanned aerial vehicles are becoming promising platforms for disaster relief, such as providing emergency communication services in wireless sensor networks, delivering some living supplies, and mapping for disaster recovery. Dynamic task scheduling plays a very critical role in coping with emergent tasks. To solve the multi-UAV dynamic task scheduling, this paper constructs a multi-constraint mathematical model for multi-UAV dynamic task scheduling, involving task demands and platform capabilities. Three objectives are considered, which are to maximize the total profit of scheduled tasks, to minimize the time consumption, and to balance the number of scheduled tasks for multiple UAVs. The multi-objective problem is converted into single-objective optimization via the weighted sum method. Then, a novel dynamic task scheduling method based on a hybrid contract net protocol is proposed, including a buy-sell contract, swap contract, and replacement contract. Finally, extensive simulations are conducted under three scenarios with emergency tasks, pop-up obstacles, and platform failure to verify the superiority of the proposed method.
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Market-Based Multirobot Coordination: A Survey and Analysis
M. Bernardine Dias, Robert Zlot, Nidhi Kalra et al. · Proceedings of the IEEE · 2006 · 905 citations · Full text