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Citation:
　S.M. Zadeh,D.M.W Powers,K. Sammut,et al.Biogeography-Based Combinatorial Strategy for Efficient Autonomous Underwater Vehicle Motion Planning and Task-Time Management[J].Journal of Marine Science and Application,2016,(4):463-477.[doi:10.1007/s11804-016-1382-6]
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Biogeography-Based Combinatorial Strategy for Efficient Autonomous Underwater Vehicle Motion Planning and Task-Time Management

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Title:
Biogeography-Based Combinatorial Strategy for Efficient Autonomous Underwater Vehicle Motion Planning and Task-Time Management
Author(s):
S.M. Zadeh;  D.M.W Powers;  K. Sammut;  A.M. Yazdani
Affilations:
Author(s):
S.M. Zadeh;  D.M.W Powers;  K. Sammut;  A.M. Yazdani
Centre for Maritime Engineering, Control and Imaging, School of Computer Science, Engineering and Mathematics, Flinders University, Adelaide SA 5042, Australia
Keywords:
autonomous underwater vehicles|underwater missions|route planning|biogeography-based optimization|computational intelligence
分类号:
-
DOI:
10.1007/s11804-016-1382-6
Abstract:
Autonomous Underwater Vehicles (AUVs) are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the 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 advantage of the Biogeography- Based Optimization (BBO) algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.

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Memo

Memo:
Received date:2016-2-21;Accepted date:2016-5-24。
Corresponding author:S.M. Zadeh
Last Update: 2016-11-24