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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.
Journal ArticleDOI

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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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.