A Cooperative-Control-Based Underwater Target Escorting Mechanism With Multiple Autonomous Underwater Vehicles for Underwater Internet of Things

Escorting a moving object in a subsea environment with cooperative autonomous underwater vehicles (AUVs) is a typical subject in Underwater Internet of Things (UIoT) applications. It involves two issues that should be studied. First, a mobile task assignment method is required to lead the AUVs to th...

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Published inIEEE internet of things journal Vol. 8; no. 6; pp. 4403 - 4416
Main Authors Zhang, Jie, Sha, Jianfa, Han, Guangjie, Liu, Jun, Qian, Yujie
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 15.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Artificial potential field (APF)
Autonomous underwater vehicles
autonomous underwater vehicles (AUVs)
Collision avoidance
Control methods
Cooperative control
formation control
Heuristic algorithms
Internet of Things
Monitoring
Object motion
Obstacle avoidance
Potential fields
Robots
Self organizing maps
Self-organizing feature maps
self-organizing map (SOM)
target escorting
Task analysis
task assignment
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Abstract Escorting a moving object in a subsea environment with cooperative autonomous underwater vehicles (AUVs) is a typical subject in Underwater Internet of Things (UIoT) applications. It involves two issues that should be studied. First, a mobile task assignment method is required to lead the AUVs to the escorting positions; then, a formation control scheme should be utilized to safely escort the moving object to the destination. Accordingly, in this article, a comprehensive target escorting mechanism called the cooperative-control-based underwater target estimating mechanism (CUTE) is proposed, which includes a belief-function-method-based self-organizing map algorithm for task assignment and an artificial potential field-based formation control method. The task assignment method aims to establish smooth routes from the AUVs to the escort position while flexibly avoiding obstacles, and the formation control method aims to improve the monitoring coverage on the escort route by rotating the formation structure while following the moving object. Simulations show that the proposed CUTE method may be very practical in underwater target escorting scenarios.
AbstractList Escorting a moving object in a subsea environment with cooperative autonomous underwater vehicles (AUVs) is a typical subject in Underwater Internet of Things (UIoT) applications. It involves two issues that should be studied. First, a mobile task assignment method is required to lead the AUVs to the escorting positions; then, a formation control scheme should be utilized to safely escort the moving object to the destination. Accordingly, in this article, a comprehensive target escorting mechanism called the cooperative-control-based underwater target estimating mechanism (CUTE) is proposed, which includes a belief-function-method-based self-organizing map algorithm for task assignment and an artificial potential field-based formation control method. The task assignment method aims to establish smooth routes from the AUVs to the escort position while flexibly avoiding obstacles, and the formation control method aims to improve the monitoring coverage on the escort route by rotating the formation structure while following the moving object. Simulations show that the proposed CUTE method may be very practical in underwater target escorting scenarios.
Author Zhang, Jie
Qian, Yujie
Liu, Jun
Sha, Jianfa
Han, Guangjie
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SubjectTerms Algorithms
Artificial potential field (APF)
Autonomous underwater vehicles
autonomous underwater vehicles (AUVs)
Collision avoidance
Control methods
Cooperative control
formation control
Heuristic algorithms
Internet of Things
Monitoring
Object motion
Obstacle avoidance
Potential fields
Robots
Self organizing maps
Self-organizing feature maps
self-organizing map (SOM)
target escorting
Task analysis
task assignment
Title A Cooperative-Control-Based Underwater Target Escorting Mechanism With Multiple Autonomous Underwater Vehicles for Underwater Internet of Things
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