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

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• 作者：S. M. Zadeh ; D. M. W. Powers ; K. Sammut…
• 关键词：autonomous vehicles ; underwater missions ; evolutionary algorithms ; biogeography ; based optimization ; route planning· computational intelligence
• 刊名：Journal of Marine Science and Application
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：15
• 期：4
• 页码：463-477
• 全文大小：1,957 KB
• 刊物类别：Engineering
• 刊物主题：Offshore Engineering
  Machinery and Machine Elements
  Electrical Power Generation and Transmission
  Chinese Library of Science
  
• 出版者：Harbin Engineering University
• ISSN：1993-5048
• 卷排序：15

文摘

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.