Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things release_dtsnwimbofentfrhxuajv4jyq4

by Zheng Yao, Sentang Wu, Yongming Wen

Published in Sensors by MDPI AG.

2019   Volume 19, p1600

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.
In application/xml+jats format

Archived Files and Locations

application/pdf  4.1 MB
file_6avwz45xizaohmjareluddrnka
res.mdpi.com (web)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2019-04-02
Language   en ?
Container Metadata
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:  1424-8220
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 6132b1f4-7aa9-4002-a8f2-111c75fc51fd
API URL: JSON