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Energy optimised D* AUV path planning with obstacle avoidance and ocean current environment

Published online by Cambridge University Press:  22 March 2022

Bing Sun Open the ORCID record for Bing Sun [Opens in a new window] ,
Wei Zhang ,
Shiqi Li  and
Xixi Zhu
Bing Sun*
Affiliation:
Shanghai Engineering Research Center of Intelligent Maritime Search & Rescue and Underwater Vehicles, Shanghai Maritime University, Shanghai, China
Wei Zhang
Affiliation:
School of Electrical Engineering, Shanghai Dianji University, Shanghai, China
Shiqi Li
Affiliation:
Shanghai Engineering Research Center of Intelligent Maritime Search & Rescue and Underwater Vehicles, Shanghai Maritime University, Shanghai, China
Xixi Zhu
Affiliation:
Shanghai Engineering Research Center of Intelligent Maritime Search & Rescue and Underwater Vehicles, Shanghai Maritime University, Shanghai, China
*
*Corresponding author. E-mail: hmsunbing@163.com
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Abstract

For the path planning of autonomous underwater vehicles (AUVs) in the ocean environment, in addition to the planned path length and safe obstacle avoidance, it is also necessary to pay attention to the impact of ocean currents on the planned path. Therefore, this paper improves the original D* algorithm, and adds the obstacle cost item and the steering angle cost item as constraints on the basis of the original cost function, thus ensuring the navigation safety of the AUV. Considering that ocean currents have a greater impact on the energy consumption of AUVs, this paper establishes a cost model for the impact of ocean currents on AUV energy consumption and applies it to the D* path planning algorithm, so that AUVs can use ocean currents to reduce energy consumption, which can be seen through simulation experiments. The simulation results show that the improvement of the algorithm can plan an optimal energy consumption path.

Keywords

autonomous underwater vehiclesocean currentpath planningD* algorithmenergy consumption optimisation

Information

Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 3 , May 2022 , pp. 685 - 703
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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