Intelligent Path Planning Technologies of Underwater Vehicles: a Review

An, Dong; Mu, Yizhuo; Wang, Yaqian; Li, Baoke; Wei, Yaoguang

doi:10.1007/s10846-022-01794-y

Cited by 19 publications

(9 citation statements)

References 118 publications

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“…In [69] the authors comprehensively introduce intelligent path planning technologies in the context of underwater vehicle path planning, emphasizing collaborative and coverage path planning. Another research paper [70] presents a scalable technique that couples and manipulates chaotic systems to improve scanning coverage efficiency in unknown environments, demonstrating a significant performance boost compared to existing planners. Another innovative approach, D-RRT*, addresses the slow convergence issue of RRT* algorithm by focusing on the direction of the goal, resulting in improved performance metrics in cluttered 2D environments [71].…”

Section: Journal Ofmentioning

confidence: 99%

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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In this paper, we introduce an efficient path planning algorithm designed for floor cleaning applications, utilizing the concept of Spanning Tree Coverage (STC). We operate under the assumption that the environment, i.e., the floor, is initially unknown to the robot, which also lacks knowledge regarding obstacle positions, except for the workspace boundaries. The robot executes alternating phases of exploration and coverage, leveraging the local map generated during exploration to construct a STC tree, which then guides the subsequent coverage (cleaning) phase. The extent of exploration is determined by the range of the robot's sensors. The path generation algorithms for cleaning fall within the broader category of coverage path planning (CPP) algorithms. A key advantage of this algorithm is that the robot returns to its initial position upon completing the operation, minimizing battery usage since sensors are only active during the exploration phase. We classify the proposed algorithm as an offline-online scheme. To validate the effectiveness and non-repetitive nature of the algorithm, we conducted simulations using VRep/MATLAB environments and implemented real-time experiments using Turtlebot in the ROS-Gazebo environment. The results substantiate the completeness of coverage and underscore the algorithm's significance in applications akin to floor cleaning.

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Section: Journal Ofmentioning

confidence: 99%

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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“…Ref. [ 112 ]’s applications of the ABC algorithm can be seen in many situations where MR (moving robot) systems operate in static environments [ 113 , 114 ]. For example, they tested a wheeled MR underwater [ 115 ], applying it to the routing problem of autonomous vehicles [ 116 ], as well as aerial robots [ 117 ].…”

Section: Heuristic Approachmentioning

confidence: 99%

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

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Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra’s algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

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“…A novel underwater glider was also analyzed through experiments during their study. An et al [42] presented a review of intelligent path-planning technologies for UUVs. The characteristics of the used algorithms in the present underwater vehicle path planning were discussed in detail.…”

Section: Uuv Control System Designmentioning

confidence: 99%

A Review of the Various Control Algorithms for Trajectory Control of Unmanned Underwater Vehicles

Bashir,

Khan,

Iqbal

et al. 2023

Sustainability

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Unmanned underwater vehicles (UUVs) have become increasingly popular in recent years due to their use in various applications. The motivations for using UUVs include the exploration of difficult and dangerous underwater environments, military tasks in mine detection, intelligence gathering and surveillance, the inspection of offshore oil and gas infrastructure in the oil and gas industry, scientific research for studying marine life, and the search and rescue of missing persons or submerged airplanes or boats in underwater environments. UUVs offer many advantages in achieving the desired applications with increased safety, efficiency, and cost-effectiveness. However, there are also several challenges associated with their communication, navigation, power requirements, maintenance, and payload limitations. These types of vehicles are also prone to various disturbances caused by currents of the ocean, propulsion systems, and unmolded uncertainties. Practically, it is a challenging task to design a controller that will ensure optimal performance under these conditions. Therefore, the control system design is of prime importance in the overall development of UUVs. Also, the UUV controller receives input from different sensors, and the data from these sensors are used by the controller to perform different tasks. The control systems of UUVs should take into account all uncertainties and make them stable so that all sensors can perform optimally. This paper presents a complete review of different control system design algorithms for UUVs. The basic logic designs of several control system algorithms are also presented. A comparison is made based on reliability, robustness, precession, and the ability of the controller to handle the nonlinearity that is faced by UUVs during their missions. Simulation and experimental results are thoroughly studied to gain insight into each algorithm. The advantages and disadvantages of each algorithm are also presented, which will facilitate the selection of a suitable algorithm for the control system design of UUVs.

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Intelligent Path Planning Technologies of Underwater Vehicles: a Review

Cited by 19 publications

References 118 publications

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

A Review of the Various Control Algorithms for Trajectory Control of Unmanned Underwater Vehicles

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