Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

Taheri, Ehsan; Ferdowsi, Mohammad Hossein; Danesh, Mohammad

doi:10.1016/j.apor.2018.12.008

Cited by 39 publications

(13 citation statements)

References 26 publications

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“…e movement of AUV is restricted by the vehicle's inherent turning constraints, such as turning rate and turning radius [44,100,106]. ey are closely related and represent the turning ability of AUV.…”

Section: Turning Constraintsmentioning

confidence: 99%

Research Progress of Path Planning Methods for Autonomous Underwater Vehicle

Guo

Liu

Fan

et al. 2021

Mathematical Problems in Engineering

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Path planning is a key technology for autonomous underwater vehicle (AUV) navigation. With the emphasis and research on AUV, AUV path planning technology is continuously developing. Path planning techniques generally include environment modelling methods and path planning algorithms. Based on a brief description of the environment modelling methods, this paper focuses on the path planning algorithms commonly used by AUV. According to the basic principles of the algorithm, the AUV path planning algorithms are divided into four categories: artificial potential field methods, geometric model search methods, random sampling methods, and intelligent bionic methods. In this review, we summarize in detail the development and application of various path planning algorithms in recent years. Meanwhile, we analyse the advantages and disadvantages of various algorithms and their improvement methods. Obstacles, ocean currents, and undersea terrain have an impact on AUV path planning. Therefore, how to deal with the complex underwater environment adds some limits to AUV path planning algorithms. In addition to the external environment, path planning algorithms also need to consider AUV’s physical constraints, such as energy constraints and motion constraints. Then, we analyse the motion constraints in AUV path planning. Finally, we discuss the development direction of AUV path planning algorithm. Time-varying ocean currents, special obstacles, multiobjective constraints, and practicability will be the problems that AUV path planning algorithms need to solve.

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Section: Turning Constraintsmentioning

confidence: 99%

Research Progress of Path Planning Methods for Autonomous Underwater Vehicle

Guo

Liu

Fan

et al. 2021

Mathematical Problems in Engineering

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“…Here, three fuzzy proportional-derivative controllers (FPDCs) are designed for the AUV heading and diving control. 27 Each of them consists of two inputs, one output, and twenty-one rules. These rules are constructed based on the designer experience, AUV dynamic constraints (Table II) In the direct course test, angles of the rudder and elevator are fixed at zero and the surge speed of the AUV is stabilized.…”

Section: Design Heading and Diving Controller Through The Fuzzy Propomentioning

confidence: 99%

Design Boundary Layer Thickness and Switching Gain in SMC Algorithm for AUV Motion Control

2019

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SummaryDesigning the boundary layer thickness and switching gain in the nonlinear part of sliding mode controller (SMC) is one of the main subjects in SMC design that needs human experience, knowledge on the amplitude of disturbances, and information about the bounds of system uncertainties. In this paper, to reduce the trial-and-error effort by the designer(s) two different fitness functions in the horizontal and vertical planes are presented and a heuristic method is used for their optimization. The optimal switching gain in the proposed approach properly compensates the unmodeled dynamics, model uncertainty, and external disturbances. Chattering phenomenon in control signals and noise measurement effect are reduced by the optimal selection of boundary layer thickness. This proposed method is applied to an autonomous underwater vehicle (AUV) and evaluated through the real-time and cost-effective manner. The execution code is implemented on a single-board computer (SBC) through the xPC Target and is evaluated by the processor-in-the-loop (PIL) test. The results of the PIL test in the two different test cases indicate that the chattering phenomenon and amplitude of control signal applied to the actuators are reduced in comparison with the three conventional approaches in the AUV motion control.

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“…Due to the low speed motion of AUV, earth's motion could be neglected. Therefore, a point on the surface of the earth can be assumed to be fixed and applied as the center of the earth-fixed coordinate system [32]. In the earth-fixed coordinate, let (x G , y G , z G ) describe the AUV's center of gravity, and (φ, θ, ψ) represent the orientation.…”

Section: Establishing Coordinate Systemmentioning

confidence: 99%

3DOF Adaptive Line-Of-Sight Based Proportional Guidance Law for Path Following of AUV in the Presence of Ocean Currents

et al. 2019

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In order to achieve high-precision path following of autonomous underwater vehicle (AUV) in the horizontal plane, a three degrees-of-freedom adaptive line-of-sight based proportional (3DOFAPLOS) guidance law is proposed. Firstly, the path point coordinate system is introduced, which is suitable for the conversion of an arbitrary path. Then, the appropriate look-ahead distance is obtained by an improved adaptive line-of-sight (ALOS) according to three degrees-of-freedom (3DOF), including the cross-track error, the curvature of reference path, and the forward speed. Moreover, combining three degrees-of-freedom ALOS (3DOFALOS) with proportional guidance law, the desired heading is calculated considering the drift angle. 3DOFAPLOS has two functions: in the convergence stage, 3DOFALOS plays a leading role, making AUV converge to the path more quickly and smoothly. In the guidance stage, proportional guidance law plays a major role in effectively resisting the influence of drift angle and making AUV sail along the reference path. If the path is curved, 3DOFALOS makes contributions in both stages, adjusting look-ahead distance in real time with respect to curvature. The stability of the designed closed system is proved by Lyapunov theory. Both simulation and experiment results have verified that 3DOFAPLOS has a satisfactory result, which improves tracking performance more than 50% compared with the traditional line-of-sight (LOS). Specifically, the mean average error (MAE) of path following under 3DOFAPLOS can be reduced by about 60%, and the root mean square error (RMSE) can be reduced by about 50% compared with LOS.

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Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

Cited by 39 publications

References 26 publications

Research Progress of Path Planning Methods for Autonomous Underwater Vehicle

Research Progress of Path Planning Methods for Autonomous Underwater Vehicle

Design Boundary Layer Thickness and Switching Gain in SMC Algorithm for AUV Motion Control

3DOF Adaptive Line-Of-Sight Based Proportional Guidance Law for Path Following of AUV in the Presence of Ocean Currents

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