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• W2951033459 abstract "SUMMARY Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario." @default.
• W2951033459 created "2019-06-27" @default.
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• W2951033459 date "2020-07-16" @default.
• W2951033459 modified "2023-10-01" @default.
• W2951033459 title "ARCog: An Aerial Robotics Cognitive Architecture" @default.
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• W2951033459 doi "https://doi.org/10.1017/s0263574720000521" @default.
• W2951033459 hasPublicationYear "2020" @default.
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