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Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

Version 2 2024-06-05, 02:16
Version 1 2019-02-13, 09:05
journal contribution
posted on 2024-06-05, 02:16 authored by Somaiyeh MahmoudZadehSomaiyeh MahmoudZadeh, DMW Powers, K Sammut, AM Yazdani
Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle’s mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

History

Journal

Journal of marine science and application

Volume

15

Pagination

463-477

Location

Berlin, Germany

ISSN

1671-9433

eISSN

1993-5048

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2016, Harbin Engineering University and Springer-Verlag Berlin Heidelberg

Issue

4

Publisher

Springer