Path Planning Method Based on D lite Algorithm for Unmanned Surface Vehicles in Complex Environments

In recent decades, path planning for unmanned surface vehicles (USVs) in complex environments, such as harbours and coastlines, has become an important concern. The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with...

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Bibliographic Details
Published in:China ocean engineering 2021-07, Vol.35 (3), p.372-383
Main Authors: Yao, Yan-long, Liang, Xiao-feng, Li, Ming-zhi, Yu, Kai, Chen, Zhe, Ni, Chong-ben, Teng, Yue
Format: Article
Language:English
Subjects:
Algorithms
Barriers
Changing environments
Coastal Sciences
Computing time
Engineering
Environmental changes
Fluid- and Aerodynamics
Harbors
Marine & Freshwater Sciences
Numerical and Computational Physics
Oceanography
Offshore Engineering
Path planning
Potential fields
Real time
Simulation
Surface vehicles
Unmanned vehicles
Vehicles
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Summary:In recent decades, path planning for unmanned surface vehicles (USVs) in complex environments, such as harbours and coastlines, has become an important concern. The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles. In this study, we developed a novel path planning method based on the D* lite algorithm for real-time path planning of USVs in complex environments. The proposed method has the following advantages: (1) the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles; (2) a constrained artificial potential field method is employed to enhance the safety of the planned paths; and (3) the method is practical in terms of vehicle performance. The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms. The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.
ISSN:0890-5487
2191-8945
DOI:10.1007/s13344-021-0034-z