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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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Decision-making for the autonomous navigation of USVs based on deep reinforcement learning under IALA maritime buoyage system

TL;DR: In this article , the authors designed a mixed environment model including multiple ocean buoys according to the IALA maritime buoyage system, and used the deep neural network to extract the state features of the target, and setting the reward function reasonably, the USV can not only navigate to the target autonomously, but also identify the corresponding buoy and give the corresponding decision.
Journal ArticleDOI

Path Planning of Unmanned Helicopter in Complex Dynamic Environment Based on State-Coded Deep Q-Network

TL;DR: In this paper , a state-coded deep Q-network (SC-DQN) algorithm with symmetric properties is proposed, which can effectively avoid randomly moving obstacles and plan a safe path for UH.
Journal ArticleDOI

An Improved Bald Eagle Search Algorithm for Global Path Planning of Unmanned Vessel in Complicated Waterways

TL;DR: In this article , a self-adaptive hybrid Bald Eagle Search (SAHBES) algorithm is proposed to improve the fitness function by adding a distance between the ships' path corners.
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A second-order dynamic and static ship path planning model based on reinforcement learning and heuristic search algorithms

TL;DR: Wang et al. as mentioned in this paper proposed a second-order ship path planning model, which consists of two main steps, i.e., first-order static global path planning and secondorder dynamic local path planning.
Journal ArticleDOI

State-dependent finite-time controller design and its application to positioning control task for underactuated unmanned surface vehicles

Qu Yang, +1 more
- 01 Jan 2023 - 
TL;DR: In this paper , an accurate state-depended finite-time positioning control framework is proposed for underactuated unmanned surface vehicles (USVs), where three control objectives have been developed to guide the surge, sway, and yaw motions, where the surge motion is directly controlled by the USV propulsion system.
References
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Genetic Algorithms

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A Formal Basis for the Heuristic Determination of Minimum Cost Paths

TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
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Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
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TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
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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.