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      Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

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          Abstract

          Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation safety distance, and formation evaluation indicators are taken into consideration. The application of the IoT enables the optimization of distributed computing. To ensure the reliability of the formation algorithm, the convergence of MAHSCO has been proved. Finally, computer simulation and actual unmanned aerial vehicle (UAV) formation generation flight generating four typical formations are carried out. The result of the actual UAV formation generation flight is consistent with the simulation experiment, and the algorithm performs well. The MAHSCO algorithm based on the IoT is proved to be able to generate formations that meet the mission requirements quickly and accurately.

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          Future paths for integer programming and links to artificial intelligence

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            Minimization by Random Search Techniques

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              UAV-Based IoT Platform: A Crowd Surveillance Use Case

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                02 April 2019
                April 2019
                : 19
                : 7
                : 1600
                Affiliations
                [1 ]School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China; woost@ 123456buaa.edu.cn
                [2 ]Science and Technology on Information Systems Engineering Laboratory, Beijing Institute of Control & Electronics Technology, Beijing 100038, China; wenyongming_buaa@ 123456foxmail.com
                Author notes
                [* ]Correspondence: by1403130@ 123456buaa.edu.cn ; Tel.: 86-010-8233-9193
                Article
                sensors-19-01600
                10.3390/s19071600
                6479587
                30987038
                294ff3b5-2e88-4fd3-9822-5bd8f35f264f
                © 2019 by the authors.

                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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 04 March 2019
                : 29 March 2019
                Categories
                Article

                Biomedical engineering
                internet of things,formation generation,distributed information fusion,autonomous collaboration,social cognitive optimization,multi-agent system

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