The role of autonomous underwater vehicles for marine search and rescue operations

Murphy, AJ; Landamore, MJ; Birmingham, RW

doi:10.3723/ut.27.195

Cited by 16 publications

(5 citation statements)

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“…Unmanned underwater vehicles (UUV) have recently gained great importance due to their role in carrying out tasks that are sometimes difficult for humans to perform on their own. These systems have important scientific applications [1][2][3][4], and military applications [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Low-cost noise maker for testing acoustically guided unmanned vehicles

Mousa,

Tork,

Abdallah

2023

J. Phys.: Conf. Ser.

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Testing the performance of the Acoustically Guided Unmanned Underwater Vehicle (AGUUV) prior to its deployment is essential to ensure its ability to perform the required tasks accurately. These systems can be deployed from boats or helicopters to scan areas of military and economic importance for threats. These threats such as aircrafts carriers, ships, submarines, divers, and autonomous surface vehicles. The problem of implementing a low-cost high-performance noise maker (LCNM) which is suitable for being used as a test target instead of different threats for AGUUVs is the motivation of this paper. Lab experiments and sea trials are performed using the proposed noise maker to demonstrate the proper operation of the AGUUV. Lab experiments showed that the radiated noise of the proposed noise maker has high power in the frequency band between 5 to 8 kHz. The measured signal to noise ratio (SNR) for the introduced LCNM is 30 dB in this band. The experimental results presented in this paper show the feasibility of using the proposed LCNM effectively to test the AGUUVs.

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Section: Introductionmentioning

confidence: 99%

Low-cost noise maker for testing acoustically guided unmanned vehicles

Mousa,

Tork,

Abdallah

2023

J. Phys.: Conf. Ser.

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“…Therefore, the application prospect of autonomous underwater vehicle is very broad [1][2][3]. When the underwater vehicle works in the marine environment, it will be affected by various uncertain factors [4], such as marine organisms, ocean current disturbances, uncertain obstacles, etc., resulting in poor stability and dynamic characteristics of the underwater vehicle [5][6][7]. Guerrero et al [8] introduced a second-order sliding mode controller (SMC) named "generalized super-twisting algorithm (GSTA)" for automatic gain adjustment to cope with external disturbances along with uncertain dynamic errors.…”

Section: Introductionmentioning

confidence: 99%

Optimal Disturbance Suppression of Disturbed Underwater Vehicle With State Delay

Liu¹,

Xu²,

Yang³

et al. 2022

IEEE Access

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In this paper, the optimal disturbance suppression problem of disturbed underwater vehicle with state delay is studied. Firstly, we establish the mathematical model of the motion of the disturbed underwater vehicle and linearize it. Secondly, the mathematical model with state delay is transformed into a formal mathematical model without time-delay by using the no time-delay transformation method. Then, according to the optimal control theory, the optimal disturbance suppression control law of the disturbed underwater vehicle with state delay is designed based on the quadratic performance index. This control law can be obtained by solving the Riccati matrix equation and Sylvester matrix equation. Finally, the effectiveness of the method is verified by an AUV system simulation example.

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“…For instance, in marine search operations, small unmanned submarines cannot access global positioning system (GPS) while underwater. And although they might be able to exchange information with a fully equipped surface vessel for centralized coordination, their typically limited bandwidth communication may impair operation effectiveness [3]. In agricultural robotics also, ground robots operate in crop fields where they receive noisy GPS data, and while they can communicate with a centralized computer station outside the field, they typically do so with limited and sometimes unreliable bandwidth [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Centralized model predictive control with distributed adaptation

Mishra¹,

Wang²,

Gazzola³

et al. 2020

Preprint

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A centralized model predictive controller (MPC), which is unaware of local uncertainties, for an affine discrete time nonlinear system is presented. The local uncertainties are assumed to be matched, bounded and structured. In order to encounter disturbances and to improve performance an adaptive control mechanism is employed locally. The proposed approach ensures input-to-state stability of closed-loop states and convergence to the equilibrium point. Moreover, uncertainties are learnt in terms of the given feature basis by using adaptive control mechanism. In addition, hard constraints on state and control are satisfied.

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The role of autonomous underwater vehicles for marine search and rescue operations

Cited by 16 publications

References 0 publications

Low-cost noise maker for testing acoustically guided unmanned vehicles

Low-cost noise maker for testing acoustically guided unmanned vehicles

Optimal Disturbance Suppression of Disturbed Underwater Vehicle With State Delay

Centralized model predictive control with distributed adaptation

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