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Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives

This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial intelligence (AI), machine learning (ML), and robot...

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Detalles Bibliográficos
Autores principales: Hagos, Desta Haileselassie, Rawat, Danda B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9782095/
https://www.ncbi.nlm.nih.gov/pubmed/36560285
http://dx.doi.org/10.3390/s22249916
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author Hagos, Desta Haileselassie
Rawat, Danda B.
author_facet Hagos, Desta Haileselassie
Rawat, Danda B.
author_sort Hagos, Desta Haileselassie
collection PubMed
description This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial intelligence (AI), machine learning (ML), and robot technologies, and their potential for developing safe and robust autonomous systems in the context of future military and defense applications. Additionally, we discuss some of the technical and operational critical challenges that arise when attempting to practically build fully autonomous systems for advanced military and defense applications. Our paper provides the state-of-the-art advanced AI methods available for tactical autonomy. To the best of our knowledge, this is the first work that addresses the important current trends, strategies, critical challenges, tactical complexities, and future research directions of tactical autonomy. We believe this work will greatly interest researchers and scientists from academia and the industry working in the field of robotics and the autonomous systems community. We hope this work encourages researchers across multiple disciplines of AI to explore the broader tactical autonomy domain. We also hope that our work serves as an essential step toward designing advanced AI and ML models with practical implications for real-world military and defense settings.
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spelling pubmed-97820952022-12-24 Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives Hagos, Desta Haileselassie Rawat, Danda B. Sensors (Basel) Article This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial intelligence (AI), machine learning (ML), and robot technologies, and their potential for developing safe and robust autonomous systems in the context of future military and defense applications. Additionally, we discuss some of the technical and operational critical challenges that arise when attempting to practically build fully autonomous systems for advanced military and defense applications. Our paper provides the state-of-the-art advanced AI methods available for tactical autonomy. To the best of our knowledge, this is the first work that addresses the important current trends, strategies, critical challenges, tactical complexities, and future research directions of tactical autonomy. We believe this work will greatly interest researchers and scientists from academia and the industry working in the field of robotics and the autonomous systems community. We hope this work encourages researchers across multiple disciplines of AI to explore the broader tactical autonomy domain. We also hope that our work serves as an essential step toward designing advanced AI and ML models with practical implications for real-world military and defense settings. MDPI 2022-12-16 /pmc/articles/PMC9782095/ /pubmed/36560285 http://dx.doi.org/10.3390/s22249916 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hagos, Desta Haileselassie
Rawat, Danda B.
Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title_full Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title_fullStr Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title_full_unstemmed Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title_short Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives
title_sort recent advances in artificial intelligence and tactical autonomy: current status, challenges, and perspectives
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9782095/
https://www.ncbi.nlm.nih.gov/pubmed/36560285
http://dx.doi.org/10.3390/s22249916
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