The optimal route planning for inspection task of autonomous underwater vehicle composed of MOPSO-based dynamic routing algorithm in currents

•A modular structure is applied to program design of the system by using the graphical language, LabVIEW®, which is composed of 6-DOF motion module, a self-tuning fuzzy control module, a stereo-vision detection module, and a dynamic routing module.•The application of image detection technique with M...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Applied ocean research Ročník 75; s. 178 - 192
Hlavní autoři: Lin, Yu-Hsien, Huang, Lin-Chin, Chen, Shao-Yu, Yu, Chao-Ming
Médium: Journal Article
Jazyk:angličtina
Vydáno: Barking Elsevier Ltd 01.06.2018
Elsevier BV
Témata:
Algorithms
Autonomous underwater vehicles
Detection
Dynamic routing algorithm
Energy consumption
Fuzzy control
Fuzzy logic
Image detection
Inspection
Mathematical models
MOPSO
Offshore
Routing
Underwater exploration
Underwater inspection
Underwater structures
Underwater vehicles
Vision
Weight
Wind farms
Wind power
MOPSO
Underwater inspection
Fuzzy control
Dynamic routing algorithm
Image detection
ISSN:0141-1187, 1879-1549
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:•A modular structure is applied to program design of the system by using the graphical language, LabVIEW®, which is composed of 6-DOF motion module, a self-tuning fuzzy control module, a stereo-vision detection module, and a dynamic routing module.•The application of image detection technique with MOPSO-based dynamic routing algorithm to optimal route plans of autonomous underwater vehicles (AUVs) in ocean currents has been validated.•In the existence of ocean currents, MOPSO with dynamic weight would have better performance and stability of cruise than those with fixed weights. For supporting the dynamic routing plan more efficiently, this study has been established by integrating PSO (Particle Swarm Optimization) −based dynamic routing algorithm, self-tuning fuzzy controller, a stereo-vision detection technique and 6-DOF mathematical model into the inspection system of AUV (Autonomous Underwater Vehicle). Specifically, the PSO-based dynamic routing algorithm is modified by adopting the concept of Multi-Objective Particle Swarm Optimization (MOPSO), which is able to handle different weights of objectives in parallel. Therefore, a modular structure is applied to program design of the system by using the graphical language, LabVIEW®, which is composed of 6-DOF motion module, a self-tuning fuzzy control module, a stereo-vision detection module, and a dynamic routing module. Performances resulted from the MOPSO-based dynamic routing algorithm would be discussed by conducting a series of inspection tasks in the imitated offshore wind farm. Additionally, selections of fixed weight and dynamic weight of MOPSO-based dynamic routing algorithm would be compared via Pareto frontiers for feasible solutions of both sailing time and energy consumption. Eventually, it is verified that the MOPSO-based dynamic routing algorithm in our system is not only able to estimate the feasible routes intelligently, but also identify features of underwater structures for the purpose of positioning.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0141-1187
1879-1549
DOI:10.1016/j.apor.2018.03.016