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Article

Hybrid Path Planning Using a Bionic-Inspired Optimization Algorithm for Autonomous Underwater Vehicles

by
Sarada Prasanna Sahoo
1,*,
Bikramaditya Das
2,
Bibhuti Bhusan Pati
1,
Fausto Pedro Garcia Marquez
3,* and
Isaac Segovia Ramirez
3
1
Department of Electrical Engineering, VSSUT, Burla 768018, India
2
Department of Electronics and Telecommunication Engineering, VSSUT, Burla 768018, India
3
Ingenium Research Group, Universidad Castilla-La Mancha, Campus Universitario s/n, 13071 Ciudad Real, Spain
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2023, 11(4), 761; https://doi.org/10.3390/jmse11040761
Submission received: 14 February 2023 / Revised: 6 March 2023 / Accepted: 21 March 2023 / Published: 31 March 2023
(This article belongs to the Special Issue AI for Navigation and Path Planning of Marine Vehicles)
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Abstract

This research presents a hybrid approach for path planning of autonomous underwater vehicles (AUVs). During path planning, static obstacles affect the desired path and path distance which result in collision penalties. In this study, the merits of grey wolf optimization (GWO) and genetic algorithm (GA) of bionic-inspired algorithms are integrated to implement a hybrid grey wolf optimization (HGWO) algorithm which allows AUVs to reach their destination safely in an obstacle rich environment. The proposed hybrid path planner is employed for path planning of a single AUV based on collision avoidance. It uses the GA as an initialization generator to overcome the random initialization problem of GWO. In this research, the total cost is considered to be a function of path distance and collision penalties. Further, the application of the proposed hybrid path planner is extended for cooperative path planning of AUVs while avoiding collision using communication consensus. Simulation results are obtained for both a single AUV and multiple AUV path planning in a 3D obstacle rich environment using a proportional-derivative controller. The Kruskal–Wallis test is employed for a non-parametric statistical analysis, where the independence of the results given by the algorithms is demonstrated.
Keywords: autonomous underwater vehicle (AUV); cooperative path planning; genetic algorithm (GA); grey wolf optimization (GWO); proportional-derivative controller autonomous underwater vehicle (AUV); cooperative path planning; genetic algorithm (GA); grey wolf optimization (GWO); proportional-derivative controller

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MDPI and ACS Style

Sahoo, S.P.; Das, B.; Pati, B.B.; Garcia Marquez, F.P.; Segovia Ramirez, I. Hybrid Path Planning Using a Bionic-Inspired Optimization Algorithm for Autonomous Underwater Vehicles. J. Mar. Sci. Eng. 2023, 11, 761. https://doi.org/10.3390/jmse11040761

AMA Style

Sahoo SP, Das B, Pati BB, Garcia Marquez FP, Segovia Ramirez I. Hybrid Path Planning Using a Bionic-Inspired Optimization Algorithm for Autonomous Underwater Vehicles. Journal of Marine Science and Engineering. 2023; 11(4):761. https://doi.org/10.3390/jmse11040761

Chicago/Turabian Style

Sahoo, Sarada Prasanna, Bikramaditya Das, Bibhuti Bhusan Pati, Fausto Pedro Garcia Marquez, and Isaac Segovia Ramirez. 2023. "Hybrid Path Planning Using a Bionic-Inspired Optimization Algorithm for Autonomous Underwater Vehicles" Journal of Marine Science and Engineering 11, no. 4: 761. https://doi.org/10.3390/jmse11040761

APA Style

Sahoo, S. P., Das, B., Pati, B. B., Garcia Marquez, F. P., & Segovia Ramirez, I. (2023). Hybrid Path Planning Using a Bionic-Inspired Optimization Algorithm for Autonomous Underwater Vehicles. Journal of Marine Science and Engineering, 11(4), 761. https://doi.org/10.3390/jmse11040761

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