Technology Development of Unmanned Underwater Vehicles (UUVs)

Heo, Jinyeong; Kim, Jung-Hoon; Kwon, Yongjin

doi:10.4236/jcc.2017.57003

Cited by 34 publications

(20 citation statements)

References 8 publications

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“…The architecture proposal follows a deterministic approach and uses an ad-hoc mission plan specification, or proposes a new one. 3 The architecture proposal follows a deterministic approach and uses either STRIPS, any of the PDDL versions or any other formal description language already defined for automated planning. 4 The architecture proposal follows a non-deterministic approach and uses an ad-hoc mission plan specification or proposes a new one.…”

Section: Category Descriptionmentioning

confidence: 99%

“…Self-adaptation is only considered at the vehicles level. 3 Self-adaptation is only considered at the global mission management level. 4…”

Section: Category Descriptionmentioning

confidence: 99%

“…The architecture does not use vehicle virtualization, and either every vehicle is considered to have the same capabilities, or they have capabilities that are tightly coupled into the architecture. 3 The architecture uses vehicle virtualization, but every vehicle is expected to have the same capabilities. 4 The architecture uses vehicle virtualization for a set of heterogeneous vehicles with different capabilities, but using a tightly coupled virtual representation.…”

Section: Category Descriptionmentioning

confidence: 99%

“…2 The architecture does not use vehicle virtualization, and either every vehicle is considered to have the same capabilities, or they have capabilities that are tightly coupled into the architecture. 3 The architecture uses vehicle virtualization, but every vehicle is expected to have the same capabilities. 4…”

Section: Category Descriptionmentioning

confidence: 99%

“…In recent years, the use of autonomous underwater vehicles (AUVs) for cooperative robotics in underwater operations has increased. This interest includes their use in military interventions [1][2][3], scientific interventions like the survey and exploration of the Arctic Ocean [4,5], and other marine interventions like, for instance, underwater infrastructure maintenance [6][7][8] and oil spill response [9][10][11]. The essential information structure for these operations has been identified as the mission.…”

Section: Introductionmentioning

confidence: 99%

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Survey of Mission Planning and Management Architectures for Underwater Cooperative Robotics Operations

et al. 2020

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Almost every research project that focuses on the cooperation of autonomous robots for underwater operations designs their own architectures. As a result, most of these architectures are tightly coupled with the available robots/vehicles for their respective developments, and therefore the mission plan and management is done using an ad-hoc solution. Typically, this solution is tightly coupled to just one underwater autonomous vehicle (AUV), or a restricted set of them selected for the specific project. However, as the use of AUVs for underwater operations increases, there is the need to identify some commonalities and weaknesses of these architectures, specifically in relation to mission planning and management. In this paper, we review a selected number of architectures and frameworks that in one way or another make use of different approaches to mission planning and management. Most of the selected works were developed for underwater operations. Still, we have included some other architectures and frameworks from other domains that can be of interest for the survey. The explored works have been assessed using selected features related to mission planning and management, considering that underwater operations are performed in an uncertain and unreliable environment, and where unexpected events are not strange. Furthermore, we have identified and highlighted some potential challenges for the design and implementation of mission managers. This provides a reference point for the development of a mission manager component to be integrated in architectures for cooperative robotics in underwater operations, and it can serve for the same purposes in other domains of application.

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Section: Category Descriptionmentioning

confidence: 99%

“…Self-adaptation is only considered at the vehicles level. 3 Self-adaptation is only considered at the global mission management level. 4…”

Section: Category Descriptionmentioning

confidence: 99%

Section: Category Descriptionmentioning

confidence: 99%

Section: Category Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Survey of Mission Planning and Management Architectures for Underwater Cooperative Robotics Operations

et al. 2020

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Modeling and adaptive controlling of cable‐drogue docking system for autonomous underwater vehicles

Liu

et al. 2021

Adaptive Control & Signal

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In this article, a novel cable-drogue docking system is proposed between an autonomous underwater vehicle (AUV) and one mobile underwater platform, to increase the docking safety and reduce the negative influences of turbulences around the platform shell on the AUV. The mathematical model of the cable-drogue system and an radial basis function neural network (RBFNN)-based Q-learning proportional-integral-differential (PID) controller are developed for the system characteristics analysis and the stabilized control. First, the cable-drogue's mathematical model is established as a link-joint-connected system, whose kinematic and dynamic equations are derived subjected to the hydrodynamic forces on system. One numerical solution procedure is also presented to obtain the motion state of the cable-drogue system. Next, considering the current interferences on the cable-drogue system, a cross rudder is added on the drogue to enhance the robustness. An RBFNN-based Q-learning PID controller is proposed to improve the control performances, in which the control parameters are adaptively optimized by an Q-learning neural network. Finally, numerical simulations are made to study the steady-state and dynamic characteristics of the cable-drogue system in ocean environment, and to investigate the performances of both the traditional PID controller and the proposed RBFNN-based Q-learning PID controller in unknown dynamical system. Simulation results show the effectiveness of the kinematic and dynamic equations of the cable-drogue system and the proposed controller in this article.

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Autonomous Weapons

Marwala,

Mpedi

2024

Artificial Intelligence and the Law

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Technology Development of Unmanned Underwater Vehicles (UUVs)

Cited by 34 publications

References 8 publications

Survey of Mission Planning and Management Architectures for Underwater Cooperative Robotics Operations

Survey of Mission Planning and Management Architectures for Underwater Cooperative Robotics Operations

Modeling and adaptive controlling of cable‐drogue docking system for autonomous underwater vehicles

Autonomous Weapons

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