A Disaster Relief UAV Path Planning Based on APF-IRRT Fusion Algorithm

Unmanned Aerial Vehicle (UAV) path planning has increasingly become the key research point for civilian drones to expand their use and enhance their work efficiency. Focusing on offline derivative algorithms, represented by Rapidly-exploring Random Trees (RRT), are widely utilized due to their high...

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Vydané v:Drones (Basel) Ročník 7; číslo 5; s. 323
Hlavní autori: Diao, Qifeng, Zhang, Jinfeng, Liu, Min, Yang, Jiaxuan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.05.2023
Predmet:
Adaptive search techniques
Algorithms
Artificial Potential Field algorithm
China
Computational efficiency
Computing time
Control systems
Convergence
Directivity
Disaster relief
Drone aircraft
Efficiency
Optimization
Path planning
Potential fields
R&D
Rapidly-exploring Random Trees algorithm
Research & development
Technology application
UAV path planning
Unmanned aerial vehicles
China
ISSN:2504-446X, 2504-446X
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Shrnutí:Unmanned Aerial Vehicle (UAV) path planning has increasingly become the key research point for civilian drones to expand their use and enhance their work efficiency. Focusing on offline derivative algorithms, represented by Rapidly-exploring Random Trees (RRT), are widely utilized due to their high computational efficiency. However, deploying these offline algorithms in complex and changing disaster environments presents its own drawbacks, such as slow convergence speed, poor real-time performance, and uneven generation paths. In this paper, the Artificial Potential Field -Improved Rapidly-exploring Random Trees (APF-IRRT*) path-planning algorithm is proposed, which is applicable to disaster relief UAV cruises. The RRT* algorithm is adapted with adaptive step size and adaptive search range coupled with the APF algorithm for final path-cutting optimization. This algorithm guarantees computational efficiency while giving the target directivity of the extended nodes. Furthermore, this algorithm achieves remarkable progress in solving problems of slow convergence speed and unsmooth path in the UAV path planning and achieves good performance in both offline static and online dynamic environment path planning.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2504-446X
2504-446X
DOI:10.3390/drones7050323