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Target assignment is an important yet difficult problem in air combat. Previous methods, e.g., neural network, genetic algorithm, particle swarm optimization and ant colony algorithm for target assignment have been proved to be either too slow or not stable as far as converging to the global optimum is concerned. In this paper, Q-learning is verified to be an appropriate reinforcement learning algorithm...
Arrival sequencing and scheduling is an important decision problem for air traffic controller (ATC) in daily operations. ATCs must select an arrival route for each flight, trying to minimize the airborne delay and to satisfy the preference of airlines, while maintaining minimum separation between aircrafts to ensure safety. Without the aid of automation system, the optimal schedule that reduces delay...
In this paper, we study the time-optimal trajectory planning of a sensor attached to an unmanned aerial vehicle (UAV) to provide complete 3-dimensional coverage with applications to urban environments with 2.5-dimensional features. The basic approach is to approximate the features of interest with a set of non planar coverage surfaces and to design a motion plan that guarantees the coverage surface...
In this paper, we present a scalable, decentralized task allocation algorithm for a group of unknown number of unmanned aerial vehicles (UAVs), which are equipped with GPS receivers, synchronized clocks and radars with a finite, but known operating distance to identify neighbors. The algorithm assigns subgroups of UAVs, whose initial positions are randomly scattered in a bounded space, to a finite...
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