Abstract
For the large-scale operations of unmanned aerial vehicle (UAV) swarm and the large number of UAVs, this paper proposes a two-layer task and resource assignment algorithm based on feature weight clustering. According to the numbers and types of task resources of each UAV and the distances between different UAVs, the UAV swarm is divided into multiple UAV clusters, and the large-scale allocation problem is transformed into several related small-scale problems. A two-layer task assignment algorithm based on the consensus-based bundle algorithm (CBBA) is proposed, and this algorithm uses different consensus rules between clusters and within clusters, which ensures that the UAV swarm gets a conflict-free task assignment solution in real time. The simulation results show that the algorithm can assign tasks effectively and efficiently when the number of UAVs and targets is large.
Highlights
unmanned aerial vehicle (UAV) swarm consists of a large number of small UAVs [1], and the cooperative task and resource assignment of UAV swarm is to real-time coordinate the UAV swarm in order to achieve an overall mission objective
The consensus phase of the consensus-based bundle algorithm (CBBA) algorithm relies on coordinated communication between all UAVs, which is achieved by propagating UAVs’ bid information through the communication links
This paper proposes a two-layer task assignment algorithm based on feature weight clustering, which could decompose the large-scale task assignment problem of the UAV swarm effectively, and the efficiency of task assignment is greatly improved
Summary
UAV swarm consists of a large number of small UAVs [1], and the cooperative task and resource assignment of UAV swarm is to real-time coordinate the UAV swarm in order to achieve an overall mission objective. The consensus phase of the CBBA algorithm relies on coordinated communication between all UAVs, which is achieved by propagating UAVs’ bid information through the communication links. As the number of UAVs in the network increases, this consensus approach may overflow the network bandwidth In these works, the communication links between all UAVs have high bandwidth, low latency, low cost, and high reliability. By solving the subproblems on different levels in order, the original problem can be solved This approach may miss the best solution, it can produce satisfactory solutions in much less time than other methods. This paper proposes a two-layer task assignment algorithm based on feature weight clustering, which could decompose the large-scale task assignment problem of the UAV swarm effectively, and the efficiency of task assignment is greatly improved
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