This paper addressesthe problemsof automatically planning AutonomousUnderwater Vehicle (AUV)pathswhichbestexploit complex current data, from computational estuarine modelforecasts, whilealsoavoiding obstacles. Inparticular weexamine thepossibilities foranovel typeofAUV mission deployment infastflowing tidal river regions whichexperience bi-directional current flow. These environments are interesting in that,by choosing an appropriate pathinspaceandtime, anAUV maybothbypass adverse currents whicharetoofasttobeovercome bythe vehicle's motorsandalsoexploit favorable currents toachieve fargreater speeds thanthemotorscouldotherwise provide, while substantially saving energy. TheAUV can"ride" currents bothupanddowntheriver, enabling extended monitoring of otherwise energy-exhausting, fastflowenvironments. The paperdiscusses suitable pathparameterizations, costfunctions andoptimization techniques whichenable optimal AUV paths to be efficiently generated. Thesepathstakemaximum advantage oftheriver currents inordertominimize energy expenditure, journey timeandothercostparameters. The resulting pathplannercan automatically suggest useful alternative mission start andendtimes andlocations tothose specified bytheuser. Examples arepresented fornavigation in a simple simulation ofthefastflowing HudsonRiverwaters around Manhattan.

Optimal AUV pathplanning forextended missions incomplex, fast-flowing estuarine environments.

The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments. The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles (AUVs) because of its hostile and dynamic nature. The major constraints for path planning are limited data transmission capability, power and sensing technology available for underwater operations. The sea environment is subjected to a large set of challenging factors classified as atmospheric, coastal and gravitational. Based on whether the impact of these factors can be approximated or not, the underwater environment can be characterized as predictable and unpredictable respectively. The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner. But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted. Path planning is necessary for many applications involving AUVs. These are based upon planning safety routes with minimum energy cost and computation overheads. This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable. The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.

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A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development.

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A survey of formation control and motion planning of multiple unmanned vehicles

This article presents an algorithm termed as multiobjective dynamic rapidly exploring random (MOD-RRT*), which is suitable for robot navigation in unknown dynamic environment. The algorithm is composed of a path generation procedure and a path replanning one. First, a modified RRT* is utilized to obtain an initial path, as well as generate a state tree structure as prior knowledge. Then, a shortcuting method is given to optimize the initial path. On this basis, another method is designed to replan the path if the current path is infeasible. The suggested approach can choose the best node among several candidates within a short time, where both path length and path smoothness are considered. Comparing with other static planning algorithms, the MOD-RRT* can generate a higher quality initial path. Simulations on the dynamic environment are conducted to clarify the efficient performance of our algorithm in avoiding unknown obstacles. Furthermore, real applicative experiment further proves the effectiveness of our approach in practical applications.

MOD-RRT*: A Sampling-Based Algorithm for Robot Path Planning in Dynamic Environment

One of the largest movers of the world economy is the oil and gas industry. The industry generates billions of barrels of oil to match more than half the world’s energy demands. Production of energ...

https://journals.sagepub.com/doi/pdf/10.1177/1475921719837718

Inspection and monitoring systems subsea pipelines: A review paper:

In this study, a single autonomous underwater vehicle (AUV) aims to rendezvous with a submerged leader recovery vehicle through a cluttered and variable operating field. The rendezvous problem is transformed into a Nonlinear Optimal Control Problem (NOCP) and then numerical solutions are provided. A penalty function method is utilized to combine the boundary conditions, vehicular and environmental constraints with the performance index that is final rendezvous time. Four evolutionary based path planning methods namely Particle Swarm Optimization (PSO), Biogeography-Based Optimization (BBO), Differential Evolution (DE), and Firefly Algorithm (FA) are employed to establish a reactive planner module and provide a numerical solution for the proposed NOCP. The objective is to synthesize and analyze the performance and capability of the mentioned methods for guiding an AUV from an initial loitering point toward the rendezvous through a comprehensive simulation study. The proposed planner module entails a heuristic for refining the path considering situational awareness of environment, encompassing static and dynamic obstacles within a spatiotemporal current fields. The planner thus needs to accommodate the unforeseen changes in the operating field such as emergence of unpredicted obstacles or variability of current field and turbulent regions. The simulation results demonstrate the inherent robustness and efficiency of the proposed planner for enhancing a vehicle’s autonomy so as to enable it to reach the desired rendezvous. The advantages and shortcoming of all utilized methods are also presented based on the obtained results.

/pdf/online-path-planning-for-auv-rendezvous-in-dynamic-cluttered-3mhuu171yl.pdf

Online path planning for AUV rendezvous in dynamic cluttered undersea environment using evolutionary algorithms

A survey of underwater docking guidance systems

Expansion of today’s underwater scenarios and missions necessitates the requisition for robust decision making of the autonomous underwater vehicle (AUV); hence, design an efficient decision-making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-free-task assignment architecture encompassing a global route planner (GRP) and a local path planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively guided to the target of interest in the context of an uncertain underwater environment. The architecture involves three main modules: The GRP module at the top level deals with the task priority assignment, mission time management, and determination of a feasible route between start and destination point in a large-scale environment. The LPP module at the lower level deals with safety considerations and generates collision-free optimal trajectory between each specific pair of waypoints listed in obtained global route. Re-planning module tends to promote robustness and reactive ability of the AUV with respect to the environmental changes. The experimental results for different simulated missions demonstrate the inherent robustness and drastic efficiency of the proposed scheme in enhancement of the vehicles autonomy in terms of mission productivity, mission time management, and vehicle safety.

A novel versatile architecture for autonomous underwater vehicle’s motion planning and task assignment

IDVD-based trajectory generator for autonomous underwater docking operations

In this article, a novel active front steering (AFS) control strategy including the upper controller and the lower controller is proposed to improve the yaw stability and maneuverability for steer-by-wire (SbW) vehicles. The adaptive recursive integral terminal sliding mode (ARITSM) control is adopted in the upper controller for guaranteeing the convergence performance of both the actual sideslip angle and the yaw rate with strong robustness and fast convergence rate. Then, a fast nonsingular terminal sliding mode (FNTSM) control with extreme learning machine (ELM) estimator to estimate its equivalent control is designed in the lower controller to track the desired front wheel steering angle calculated from the upper controller for driving the sideslip angle and the yaw rate to converge ideal value. It is shown that the upper controller takes two controlled variables (vehicle sideslip angle and yaw rate) and only one control input (front steering angle) into consideration, which can obtain a better performance compared with the case of using only one of these values. Since using the ELM technique in the lower controller to estimate the equivalent control of the FNTSM, not only the dependence of SbW system dynamics can be alleviated in the process of designing controller but also the excellent steering control performance can be achieved. Comparative simulations are carried out by utilizing Carsim and Matlab software to validate the excellent performance of the proposed control strategy for different steering maneuvers.

Amirmehdi Yazdani

Papers

Online path planning for AUV rendezvous in dynamic cluttered undersea environment using evolutionary algorithms

A survey of underwater docking guidance systems

A novel versatile architecture for autonomous underwater vehicle’s motion planning and task assignment

IDVD-based trajectory generator for autonomous underwater docking operations

Active Front Steering-Based Electronic Stability Control for Steer-by-Wire Vehicles via Terminal Sliding Mode and Extreme Learning Machine