An Integrated Auv Path Planning Algorithm With Ocean Current and Dynamic Obstacles

Zhu, Daqi; Cheng, Chunlei; Sun, Bing

doi:10.2316/journal.206.2016.5.206-4570

Cited by 16 publications

(12 citation statements)

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“…A potential-field-based method in conjunction with the virtual force concept to maneuver AUV in an unknown environment has been illustrated by Ding et al [71] , that resolved the local minima problem in PFA based path following. Zhu et al [72] presented an integrated AUV PP algorithm by incorporating "velocity synthesis (VS)" and "artificial potential field (APF)" methods together.…”

Section: Potential-field Algorithm (Pfa)mentioning

confidence: 99%

“…•Provides safe and reliable path for slow moving AUVs in the coastline •Computational complexity is high Predictable Metaheuristic algorithms [53][54][55][56][57][58] Energy optimal Poor Low •Searches the solution from a large solution space •Requires effective memory management Predictable MCDA [59] Time optimal Poor Low •Provides time optimized path •Computational complexity is high Unpredictable Graphical method [60][61][62][63][64][65][66] [71,72] Time optimal Poor Low…”

Section: Achieved Lowmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Panda

Subudhi

Pati

2020

Int. J. Autom. Comput.

148

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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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Section: Potential-field Algorithm (Pfa)mentioning

confidence: 99%

Section: Achieved Lowmentioning

confidence: 99%

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Panda

Subudhi

Pati

2020

Int. J. Autom. Comput.

148

View full text Add to dashboard Cite

show abstract

“…Various algorithms should learn from each other to jointly complete the path planning task of AUV. Considering the influence of ocean current on AUV path planning, the velocity synthesis algorithm can be combined with some path planning algorithms, such as APF [17,110] and BNN [84]. In 2018, Yao and Zhao used the grey wolf optimization algorithm to modify the mutation operator in the genetic algorithm to make the mutation change to the optimal solution direction [72]; given the fact that traditional ACO algorithm is easy to fall into local optimal, Che et al designed a heuristic function based on the PSO algorithm to improve the global search efficiency [64].…”

Section: Direction B: Fusion Of Multiple Path Planning Algorithmsmentioning

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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“…It can achieve controllability in complex real-world sceneries with dynamic obstacles if a reachable configuration set exists. Zhu et al [45] take account of both the ocean current and moving obstacles influence underwater. It proposes an integrated AUV path planning algorithm through a combination of velocity synthesis (VS) and an enhanced APF algorithm.…”

Section: Introductionmentioning

confidence: 99%

Improved Artificial Potential Field Method Applied for AUV Path Planning

Fan

Guo

Liu

et al. 2020

Mathematical Problems in Engineering

134

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With the topics related to the intelligent AUV, control and navigation have become one of the key researching fields. This paper presents a concise and reliable path planning method for AUV based on the improved APF method. AUV can make the decision on obstacle avoidance in terms of the state of itself and the motion of obstacles. The artificial potential field (APF) method has been widely applied in static real-time path planning. In this study, we present the improved APF method to solve some inherent shortcomings, such as the local minima and the inaccessibility of the target. A distance correction factor is added to the repulsive potential field function to solve the GNRON problem. The regular hexagon-guided method is proposed to improve the local minima problem. Meanwhile, the relative velocity method about the moving objects detection and avoidance is proposed for the dynamic environment. This method considers not only the spatial location but also the magnitude and direction of the velocity of the moving objects, which can avoid dynamic obstacles in time. So the proposed path planning method is suitable for both static and dynamic environments. The virtual environment has been built, and the emulation has been in progress in MATLAB. Simulation results show that the proposed method has promising feasibility and efficiency in the AUV real-time path planning. We demonstrate the performance of the proposed method in the real environment. Experimental results show that the proposed method is capable of avoiding the obstacles efficiently and finding an optimized path.

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An Integrated Auv Path Planning Algorithm With Ocean Current and Dynamic Obstacles

Cited by 16 publications

References 0 publications

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Research Progress of Path Planning Methods for Autonomous Underwater Vehicle

Improved Artificial Potential Field Method Applied for AUV Path Planning

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