A Study of Collaborative Trajectory Planning Method Based on Starling Swarm Bionic Algorithm for Multi-Unmanned Aerial Vehicle

This academic paper addresses the challenges associated with trajectory planning for affordable and light-weight Unmanned Aerial Vehicle (UAV) swarms, despite limited computing resources and extensive cooperation requirements. Specifically, an imitation-based starling cluster cooperative trajectory...

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Bibliographic Details
Published in:Applied sciences Vol. 13; no. 11; p. 6795
Main Authors: Chen, Fayin, Tang, Yong, Li, Nannan, Wang, Tao, Hu, Yiwen
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.06.2023
Subjects:
Algorithms
Analysis
Birds
Collaboration
Computer simulation
Computer-generated environments
cooperative algorithms for starling imitation
cooperative control of clusters
Decision making
Drone aircraft
Genetic algorithms
Methods
Searches and seizures
Simulation methods
simulation modelling
trajectory planning
UAV clustering
Unmanned aerial vehicles
China
Germany
United States > US
ISSN:2076-3417, 2076-3417
Online Access:Get full text
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Summary:This academic paper addresses the challenges associated with trajectory planning for affordable and light-weight Unmanned Aerial Vehicle (UAV) swarms, despite limited computing resources and extensive cooperation requirements. Specifically, an imitation-based starling cluster cooperative trajectory planning technique is proposed for a fixed-wing model of a six-degree-of-freedom UAV cluster. To achieve this, dynamic trajectory prediction of the rapid random search tree is utilized to generate a track solution adapted to the terrain environment. Additionally, the Dubins aircraft path solution is applied as it is suitable for executing input track commands by the UAV model. Computational simulations on different cluster sizes show the approach can maintain the cluster state while navigating diverse terrains, with the track solution complying with the UAV’s physical model properties.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app13116795