Swarm velocity guidance based distributed finite-time coordinated path-following for uncertain under-actuated autonomous surface vehicles

Liang, Xiao; Qu, Xingru; Wang, Weining; Li, Ye

doi:10.1016/j.isatra.2020.11.025

Cited by 17 publications

(4 citation statements)

References 45 publications

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“…It successfully realized the process of multiple unmanned underwater vehicles tracking multiple parameterized paths in a complex environment. To improve the convergence time of the formation control system, literature 86 designed a distributed surge and heading dynamics controller based on an uncertainty observer under physical constraints to ensure that the USV tracks the guidance signal within a limited time.…”

Section: Musv Collaborative Round-up Methodsmentioning

confidence: 99%

Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence

Sun

et al. 2022

International Journal of Advanced Robotic Systems

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In recent years, the research of multiple unmanned surface vessels collaboration has received great attention. More and more researchers have proposed different methods of multiple unmanned surface vessels collaboration, such as cooperative collision avoidance, formation, and rendezvous. Based on the significant advantages of biological swarm intelligence applications in these collaborative methods, this article summarizes the research methods of multiple unmanned surface vessels collaborative search and hunting from the perspective of swarm intelligence. First of all, this article summarizes the key technologies of multiple unmanned surface vessels collaborative search and hunting from the aspects of the multi-robot system, group communication, environment modeling, collaboration mechanism, and path planning. Then, it reviews some classic swarm intelligence algorithms, analyzes the advantages and disadvantages of these algorithms, and proposes optimization directions for existing disadvantages based on relevant literature. Finally, the article points out some existing problems in every stage and suggestions for future research.

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Section: Musv Collaborative Round-up Methodsmentioning

confidence: 99%

Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence

Sun

et al. 2022

International Journal of Advanced Robotic Systems

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“…( 10), the set { } Step 2: Under z h with 1 z = , the positions of vehicles are initialised using Eq. ( 5) and (6). Number the vehicles ranging from 1 to f a and save the current information into the set { } A .…”

Section: Navigation Situation Assessment Designmentioning

confidence: 99%

“…Successful applications can be found in military missions, such as beeswarm warfare, countermeasure equipment and saturation attacks. Fruitful cooperative manoeuvring methods have been proposed, ranging from cooperative trajectory tracking [3,4], and cooperative path following [5,6], to cooperative hunting [7].…”

mentioning

confidence: 99%

Navigation Situation Assessment of Autonomous Surface Vehicles in a Cooperative Hunting Environment

Zhang

Wang

Gao

et al. 2022

Polish Maritime Research

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This paper proposes a navigation situation assessment method for autonomous surface vehicles (ASVs) in a cooperative hunting environment. By virtue of the repulsion function expressed in the artificial potential field, the navigation situation of hunting ASVs and target ASVs is firstly described. And the hunting situation is also constructed to describe the cooperative hunting. Based on the navigation situation and the hunting situation, a navigation situation assessment method for cooperative hunting of multiple ASVs is designed, where the number of hunting vehicles and the hunting radius can be successfully computed. Simulation results show that this proposed situation assessment method can give an optimised formation pattern and provide an effective reference for cooperative hunting of ASVs.

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“…However, AUVs in practice inevitably suffer from dynamic uncertainties and/or ocean currents. As an effective remedy of this problem, the robust control is extensively investigated such as adaptive dynamic surface control [8,9], sliding mode control [10][11][12], and finite-time control [13,14]. Besides, to reconstruct and compensate dynamic uncertainties, neural network- [15,16] and fuzzy logic system- [17,18] based state observers have also received increasing attention.…”

Section: Introductionmentioning

confidence: 99%

Region-Searching of Multiple Autonomous Underwater Vehicles: A Distributed Cooperative Path-Maneuvering Control Approach

Chen

Zhang

et al. 2021

JMSE

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In this article, a distributed cooperative path-maneuvering control approach is developed for the region-searching of multiple autonomous underwater vehicles under both dynamic uncertainties and ocean currents. Salient contributions are as follows: (1) by virtue of boustrophedon motions and trigonometric functions, the coverage path-planning design is first proposed to generate multiple parameterized paths, which can guarantee that the region-searching is successfully completed by one trial; (2) combining with sliding mode and adaptive technique, distributed maneuvering control laws for surge and yaw motions are employed to drive vehicles to track the assigned paths, thereby contributing to the cooperative maneuvering performance with high accuracy; (3) by the aid of graph theory, the distributed signal observer-based consensus protocols are developed for path parameter synchronization, and successfully apply to maintain the desired formation configuration. The globally asymptotical stability of the closed-loop signals is analyzed via the direct Lyapunov approach, and simulation studies on WL-II are conducted to illustrate the remarkable performance of the proposed path-maneuvering control approach.

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Swarm velocity guidance based distributed finite-time coordinated path-following for uncertain under-actuated autonomous surface vehicles

Cited by 17 publications

References 45 publications

Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence

Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence

Navigation Situation Assessment of Autonomous Surface Vehicles in a Cooperative Hunting Environment

Region-Searching of Multiple Autonomous Underwater Vehicles: A Distributed Cooperative Path-Maneuvering Control Approach

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