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• W4313496277 abstract "Drone swarms are being utilized in several areas, e.g., monitoring, surveillance, security, and search, demonstrating great potential. In this paper, we considered a specific number of drones flying simultaneously (using computational intelligence techniques between them to avoid collisions) and increased the effectiveness in conducting search tasks. The main contribution of this work is to propose a technique to coordinate the swarm using search methods based on the A* algorithm and its heuristics (i.e., Euclidean and Manhattan distances). The communication between drones is also evaluated and applied to a target search problem on a two-dimensional cost map. The results show a considerable optimization in the effectiveness of the drone swarm (fewer drones are blocked at local minima), which highlights the contribution of this work." @default.
• W4313496277 created "2023-01-06" @default.
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• W4313496277 date "2022-10-18" @default.
• W4313496277 modified "2023-09-23" @default.
• W4313496277 title "A-Star Based Algorithm Applied to Target Search and Rescue by a UAV Swarm" @default.
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• W4313496277 doi "https://doi.org/10.1109/lars/sbr/wre56824.2022.9996054" @default.
• W4313496277 hasPublicationYear "2022" @default.
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