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ARCog: An Aerial Robotics Cognitive Architecture

Published online by Cambridge University Press:  16 July 2020

Milena F. Pinto ,
Leonardo M. Honório ,
Andre L. M. Marcato Open the ORCID record for Andre L. M. Marcato [Opens in a new window] ,
Mario A. R. Dantas ,
Aurelio G. Melo Open the ORCID record for Aurelio G. Melo [Opens in a new window] ,
Miriam Capretz  and
Cristina Urdiales
Milena F. Pinto*
Affiliation:
Department of Electronics, Federal Center for Technological Education of Rio de Janeiro (CEFET-RJ), Rio de Janeiro, Brazil
Leonardo M. Honório
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Andre L. M. Marcato
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Mario A. R. Dantas
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Aurelio G. Melo
Affiliation:
Department of Electrical Engineering, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil
Miriam Capretz
Affiliation:
Department of Electrical and Computer Engineering, Faculty of Engineering, Western University, London, Canada
Cristina Urdiales
Affiliation:
Department of Electronics Technology, University of Málaga, Málaga, Spain
*
*Corresponding author. E-mail: milenafaria@ieee.org
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Summary

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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.

Keywords

Unmanned aerial vehicleIntelligent systemsAutonomous missionDecentralized architectureDecision-making

Information

Type
Articles
Information
Robotica , Volume 39 , Issue 3 , March 2021 , pp. 483 - 502
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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