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A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents

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This article is published in Ocean Engineering.The article was published on 2018-12-01 and is currently open access. It has received 169 citations till now.

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

TL;DR: The possibilities for a novel type of AUV mission deployment in fast flowing tidal river regions which experience bi-directional current flow are examined, enabling extended monitoring of otherwise energy-exhausting, fast flow environments.
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Fuzzy logic based dynamic decision-making system for intelligent navigation strategy within inland traffic separation schemes

TL;DR: From the results of both scenarios for overtaking and following, it illustrates that the timing is significant for strategy selection and should well consider the complex situation and ship behaviours, moreover, the proposed approach can be used for intelligent strategy selection.
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Learn to Navigate: Cooperative Path Planning for Unmanned Surface Vehicles Using Deep Reinforcement Learning

TL;DR: This work investigates the application of deep reinforcement learning algorithms for USV and USV formation path planning with specific focus on a reliable obstacle avoidance in constrained maritime environments.
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A path planning approach based on multi-direction A* algorithm for ships navigating within wind farm waters

TL;DR: Simulation results indicate that the trajectory from 20-direction A* algorithm has similar path length with real cases while enhancing navigation safety to a large degree and making a trade-off between computation complexity and efficiency.
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Global path planning and multi-objective path control for unmanned surface vehicle based on modified particle swarm optimization (PSO) algorithm

TL;DR: Simulation experiments validate that the proposed hierarchical navigation method, CSPSO algorithm, and collision avoidance rules are effective and justifiable.
References
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Proceedings ArticleDOI

Optimal AUV path planning for extended missions in complex, fast-flowing estuarine environments

TL;DR: In this paper, the authors address the problems of automatically planning autonomous underwater vehicle (AUV) paths which best exploit complex current data, from computational estuarine model forecasts, while also avoiding obstacles.
Journal ArticleDOI

Feasible and Optimal Path Planning in Strong Current Fields

TL;DR: This paper proposes here a new approach called the sliding wavefront expansion, which combines an appropriate cost function and continuous optimization techniques, and guarantees the existence of a path with an arbitrary precision.
Journal ArticleDOI

A technique for autonomous underwater vehicle route planning

TL;DR: An algorithm using artificial potential fields to aid in path planning is presented and the problem of being trapped in a local minimum is greatly reduced, allowing the method to be used for global planning.
Proceedings Article

Underwater robotics

TL;DR: Some key areas in current state-of-the-art underwater robotic technologies are described and future research direction is presented.
Journal ArticleDOI

3D path planning for underwater vehicles using five evolutionary optimization algorithms avoiding static and energetic obstacles

TL;DR: Five intelligent evolutionary algorithms (EAs), which include genetic algorithm, memetic algorithm, particle swarm optimization, ant colony optimization and shuffled frog leaping algorithm, are applied to solve the NOCP to show that the trajectories obtained by the intelligent methods are better than those of conjugate gradient method.
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Q1. What are the contributions in "A constrained a* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents" ?

Unlike existing work on USV navigation using graph based methods, this study extends the implementation of the proposed A * approach in an environment cluttered with static and moving obstacles and different current intensities. The study also examines the effect of headwind and tailwind currents moving in clockwise and anti clockwise direction respectively of different intensities on optimal waypoints in a partially dynamic environment. 

The approach is found to be robust, computationally efficient and can be extended for real time path planning of USVs in confined water. In future work, it is planned to extend the work in development of a path follower approach working in conjugation with proposed approach for a reactive path planning in scenarios involving close encounters. A challenging 28 extension of the current work lies in fact of finding a heuristic cost function which can take into account rules of the COLREGs without compromising the optimality and computational effort required to find a feasible trajectory.