A Novel Region-Construction Method for Multi-USV Cooperative Target Allocation in Air–Ocean Integrated Environments

Author:

Zhou Zeyu1,Li Mingyang2,Hao Yun3

Affiliation:

1. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China

2. Department of Mechanical Engineering, University of Hong Kong, Hong Kong 999077, China

3. School of Mathematics and Statistics, Shaanxi Normal University, Xi’an 710119, China

Abstract

The effective defense of sparsely populated border islands, surrounded by a multifaceted sea, against enemy infiltration poses a crucial problem in national defense. One possible solution is to deploy multiple unmanned surface vessels (USVs) to form an intelligent patrol and defense system. With the designated or daily patrols of USVs, we need to allocate target positions in real time to ensure their continuous operation. Currently, the state-of-art methods contain two major problems of target deadlock and local optimization, which limit the efficiency of reaching the target. To this end, we proposed a novel Region-Construction (RECO) method aimed at high-efficiency target allocation. Firstly, a dynamic calculation approach in K value for unsupervised clustering and time factor’s lead-in for Market-Based Mechanism (MBM) method was created to resolve potential target deadlock among USVs. Secondly, we proposed a novel construction strategy in a non-complete graph (NCG) consisting of neighborhood connection and pheromone extension to provide enough feasible nodes for solution searching. Finally, we introduced adjustment of search range and edge weights, and activated node interaction in traditional Ant Colony Optimization (ACO) algorithm in NCG to obtain the optimal combination of each USV’s target allocations. We established a simulation platform with an airborne managing base station and several USVs. The experimental results demonstrated that when the number of USVs was four, the average time for all USVs to reach the target in the RECO method reduced by 10.9% and 7.7% compared to the MBM and ACO methods, respectively. This reduction was 25% and 11.6% for 6 USVs, 25.7% and 21.8% for 8 USVs, 20% and 19% for 10 USVs. It reflects that the proposed RECO allocation method has shown improvements in terms of successfully-assigned USVs’ quantity and operational efficiency, compared to the state-of-art MBM and ACO algorithms.

Funder

Advanced Jet Propulsion Creativity Center

Natural Science Foundation of Shaanxi Province

Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities of China

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Reference31 articles.

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