scholarly journals Event-Based Path-Planning and Path-Following in Unknown Environments for Underactuated Autonomous Underwater Vehicles

2020 ◽  
Vol 10 (21) ◽  
pp. 7894
Author(s):  
Sergey Ulyanov ◽  
Igor Bychkov ◽  
Nikolay Maksimkin
Keyword(s):  
Control System ◽  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Discrete Event ◽  
Path Following ◽  
Level Control ◽  
Reference Path ◽  
Turning Radius ◽  
Event Based

The paper addresses path planning and path-following problems in an unknown complex environment for an underactuated autonomous underwater vehicle (AUV). The AUV is required to follow a given reference path represented as a sequence of smoothly joined lines and arcs, bypassing obstacles encountered on the path. A two-level control system is proposed with an upper level for event-driven path planning and a lower level for path-following. A discrete event system is designed to identify situations that require planning a new path. An improved waypoint guidance algorithm and a Dubins curves based algorithm are proposed to build paths that allow the AUV to avoid collision with obstacles and to return to the reference path respectively. Both algorithms generate paths that meet the minimum turning radius constraint. A robust parameter-varying controller is designed using sublinear vector Lyapunov functions to solve the path-following problem. The performance of the developed event-based control system is demonstrated in three different simulation scenarios: with a sharp-edged obstacle, with a U-shaped obstacle, and with densely scattered obstacles. The proposed scheme does not require significant computing resources and allows for easy implementation on board.

Backstepping Control Method for the Trajectory Tracking for the Underactuated Autonomous Underwater Vehicle

2013 ◽  
Vol 798-799 ◽  
pp. 484-488 ◽  
Author(s):  
Lei Wan ◽  
Nan Sun ◽  
Yu Lei Liao
Keyword(s):  
Control System ◽  
Trajectory Tracking ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Autonomous Underwater Vehicles ◽  
Path Following ◽  
Underactuated System ◽  
Strong Nonlinearity ◽  
Parameter Uncertainties ◽  
Path Following Control

The underactuated autonomous underwater vehicles (AUV) have the characteristics of strong nonlinearity and model uncertainty. A method of backstepping path following control was raised for the trajectory tracking control problem of the AUV under Serret-Frenet frame. It transformed the original underactuated system into an actuated nonlinear system based on simplified analysis. A backstepping trajectory tracking controller was proposed based on backstepping method. By means of Lyapunov stability theory, it was proven that the proposed controller can guarantee the path following control system globally asymptotically stable. Simulation experiments show that the control system has good adaptability and robustness in case of parameter uncertainties and external disturbances to avoid shaking of performance.

scholarly journals Report on Research with Biomimetic Autonomous Underwater Vehicle — Low Level Control

2018 ◽  
Vol 212 (1) ◽  
pp. 105-123
Author(s):  
Tomasz Praczyk ◽  
Piotr Szymak ◽  
Krzysztof Naus ◽  
Leszek Pietrukaniec ◽  
Stanisław Hożyń
Keyword(s):  
Research And Development ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Swimming Pool ◽  
Final Report ◽  
Level Control ◽  
Low Level

Abstract The paper presents the first part of the final report on all the experiments with biomimetic autono-mous underwater vehicle (BAUV) performed within the confines of the project entitled ‘Autonomous underwater vehicles with silent undulating propulsion for underwater ISR’, financed by Polish National Center of Research and Development. The report includes experiments in the swimming pool as well as in real conditions, that is, both in a lake and in the sea. The tests presented in this part of the final report were focused on low-level control.

Safe Navigation Algorithm for Autonomous Underwater Vehicles

2021 ◽  
Vol 29 (1) ◽  
pp. 97-110
Author(s):  
V.S. Bykova ◽  
◽  
A.I. Mashoshin ◽  
I.V. Pashkevich ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Limited Size ◽  
Safe Navigation ◽  
Navigation Algorithm ◽  
Navigation Algorithms ◽  
Ice Edge

Two safe navigation algorithms for autonomous underwater vehicles are described: algorithm for avoidance of point obstacles including all the moving underwater and surface objects, and limited size bottom objects, and algorithm for bypassing extended obstacles such as bottom elevations, rough lower ice edge, garbage patches. These algorithms are developed for a control system of a heavyweight autonomous underwater vehicle.

scholarly journals An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985318
Author(s):  
Zheng Cong ◽  
Ye Li ◽  
Yanqing Jiang ◽  
Teng Ma ◽  
Yusen Gong ◽  
...  
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Positioning Accuracy ◽  
Planning Methods ◽  
Planning Algorithms ◽  
Motion Characteristics

This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.

scholarly journals A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Jianjun Ni ◽  
Liuying Wu ◽  
Pengfei Shi ◽  
Simon X. Yang
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Planning Method ◽  
Planning Problem ◽  
Detection Range ◽  
The Real ◽  
Time Path

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Autonomous underwater vehicle path planning based on actor-multi-critic reinforcement learning

2020 ◽  
pp. 095965182093708
Author(s):  
Zhuo Wang ◽  
Shiwei Zhang ◽  
Xiaoning Feng ◽  
Yancheng Sui
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Value Function ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Learning Efficiency ◽  
Environmental Adaptability ◽  
Vehicle Path ◽  
The Value Function

The environmental adaptability of autonomous underwater vehicles is always a problem for its path planning. Although reinforcement learning can improve the environmental adaptability, the slow convergence of reinforcement learning is caused by multi-behavior coupling, so it is difficult for autonomous underwater vehicle to avoid moving obstacles. This article proposes a multi-behavior critic reinforcement learning algorithm applied to autonomous underwater vehicle path planning to overcome problems associated with oscillating amplitudes and low learning efficiency in the early stages of training which are common in traditional actor–critic algorithms. Behavior critic reinforcement learning assesses the actions of the actor from perspectives such as energy saving and security, combining these aspects into a whole evaluation of the actor. In this article, the policy gradient method is selected as the actor part, and the value function method is selected as the critic part. The strategy gradient and the value function methods for actor and critic, respectively, are approximated by a backpropagation neural network, the parameters of which are updated using the gradient descent method. The simulation results show that the method has the ability of optimizing learning in the environment and can improve learning efficiency, which meets the needs of real time and adaptability for autonomous underwater vehicle dynamic obstacle avoidance.

scholarly journals Cognition-based hybrid path planning for autonomous underwater vehicle target following

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141985755 ◽  
Author(s):  
Li Yue Ming ◽  
Huang Hai ◽  
Xu Yang ◽  
Zhang Guocheng ◽  
Li Jiyong ◽  
...  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Target Detection ◽  
Optimization Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Cognitive Architecture ◽  
Underwater Vehicle ◽  
Fuzzy Rules ◽  
Mobile Target

Intelligent path planning is one of the key techniques for autonomous underwater vehicles for the purpose of target detection, environmental survey and so on. In order to realize automatic motion plan, an intelligent cognitive architecture for autonomous underwater vehicle motion planning has been proposed to realize complicated target detection and mobile target following in the disturbance environment. A novel adaptive ant colony optimization and particle swarm optimization fusion-based fuzzy rules optimization algorithm has been proposed to generate optimized fuzzy rules. Through this optimization algorithm, the preliminary fuzzy rules can be optimized to realize intelligent motion planning for complicated operation tasks. Experiments of channel following for wall detection and mobile target following in the oceanic environment have verified the validity of path planning method in the implementation of detection and operation tasks.

Path Following of Underactuated Marine Underwater Vehicles in the Presence of Unknown Ocean Currents

2014 ◽  
Author(s):  
Signe Moe ◽  
Walter Caharija ◽  
Kristin Y. Pettersen ◽  
Ingrid Schjølberg
Keyword(s):  
Oil And Gas ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Path Following ◽  
Oil And Gas Industry ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Ocean Currents ◽  
The Arctic ◽  
Ocean Current

The use of autonomous marine vehicles, and especially autonomous underwater vehicles, is rapidly increasing within several fields of study. In particular, such vehicles can be applied for sea floor mapping, oceanography, environmental monitoring, inspection and maintenance of underwater structures (for instance within the oil and gas industry) and military purposes. They are also highly suitable for operations below ice-covered areas in the Arctic. However, there are still many challenges related to making such underwater vehicles autonomous. A fundamental task of an autonomous underwater vehicle vessel is to follow a general path in the presence of unknown ocean currents. There exist several results for underwater vehicles to follow a general path when no ocean currents are present [1] and to follow a geometrically simple path such as a straight line when ocean currents affect the vehicle [2, 3], but the problem of general path following in the presence of unknown ocean currents has not been solved yet. This paper presents a method to achieve this. The results are an extension of the results in [1], and introduce a virtual Serret-Frenet reference frame that is anchored in and propagates along the desired path. The closed-loop system consists of an ocean current observer, a guidance law, a controller and an update law to drive the Serret-Frenet frame along the path, and is shown to be asymptotically stable given that certain assumptions are fulfilled. This guarantees that the autonomous underwater vehicle will converge to the desired path and move along it with the desired velocity. Simulation results are presented to verify and illustrate the theoretical results.

An Autonomous Underwater Vehicle for Competition

2013 ◽  
Vol 380-384 ◽  
pp. 595-600
Author(s):  
Hai Tian ◽  
Bo Hu ◽  
Can Yu Liu ◽  
Guo Chao Xie ◽  
Hui Min Luo
Keyword(s):  
Control System ◽  
Hydrodynamic Model ◽  
Degrees Of Freedom ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Vertical Motion ◽  
Underwater Vehicle ◽  
Step Response ◽  
Six Degrees Of Freedom ◽  
Simulink Simulation

The research of this paper was derived from the small autonomous underwater vehicle (AUV)Raider well performed in the 15th International Underwater Vehicle Competition (IAUVC),San Diego. In order to improve the performance of underwater vehicle, the control system of performance motion played an important role on autonomous underwater vehicles stable motion, and the whole control system of AUV is the main point. Firstly, based on the motion equations of six degrees of freedom, the paper simplified the dynamical model reasonably in allusion; Due to the speed of Raider to find the target was very low, this paper considered the speed was approximately zero and only considered the vertical motion. Therefore, this paper established the vertical hydrodynamic model of Raider, obtaining the transfer equation of vertical motion. Through the experiment and Matlab/Simulink simulation, this paper got the actual depth of the step response curve and simulation curve, and verified the validity of the vertical hydrodynamic model and the correlation coefficient.

Robust generalized dynamic inversion based control of autonomous underwater vehicles

2017 ◽  
Vol 232 (4) ◽  
pp. 434-447 ◽  
Author(s):  
Uzair Ansari ◽  
Abdulrahman H Bajodah
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Closed Loop ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Dynamic Inversion ◽  
Control Law ◽  
Closed Loop System

A novel two-loop structured robust generalized dynamic inversion–based control system is proposed for autonomous underwater vehicles. The outer (position) loop of the generalized dynamic inversion control system utilizes proportional-derivative control of the autonomous underwater vehicle’s inertial position errors from the desired inertial position trajectories, and it provides the reference yaw and pitch attitude angle commands to the inner loop. The inner (attitude) loop utilizes generalized dynamic inversion control of a prescribed asymptotically stable dynamics of the attitude angle errors from their reference values, and it provides the required control surface deflections such that the desired inertial position trajectories of the vehicle are tracked. The dynamic inversion singularity is avoided by augmenting a dynamic scaling factor within the Moore–Penrose generalized inverse in the particular part of the generalized dynamic inversion control law. The involved null control vector in the auxiliary part of the generalized dynamic inversion control law is constructed to be linear in the pitch and yaw angular velocities, and the proportionality gain matrix is designed to guarantee global closed-loop asymptotic stability of the vehicle’s angular velocity dynamics. An additional sliding mode control element is included in the particular part of the generalized dynamic inversion control system, and it works to robustify the closed-loop system against tracking performance deterioration due to generalized inversion scaling, such that semi-global practically stable attitude tracking is guaranteed. A detailed six degrees-of-freedom mathematical model of the Monterey Bay Aquarium Research Institute autonomous underwater vehicle is used to evaluate the control system design, and numerical simulations are conducted to demonstrate closed-loop system performance under various types of autonomous underwater vehicle maneuvers, under both nominal and perturbed autonomous underwater vehicle system’s mathematical model parameters.

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