Collaborative Search and Package Delivery Strategy for UAV Swarms Under Area Restrictions

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ziwei Xin, Juan Li, Jie Li, Chang Liu
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引用次数: 0

Abstract

The rapid implementation of multi-task decoupling in restricted flight areas for unmanned aerial vehicle swarms is crucial to ensure swarm effectiveness. This study introduces a task-switching mechanism in the bio-inspired rule-based (Bio-RB) decision-making algorithm and establishes a mapping relationship from behavioral rules to task modes. A complete decision model is constructed for the cooperative search and package delivery tasks. To further improve the search efficiency of swarms in restricted areas, a boundary-handling strategy based on the combination of path prediction and virtual agents is proposed. The overall scheme is termed the task-driven rule-based (Task-RB) decision-making algorithm. The proposed Task-RB method is evaluated under full-flow simulation. Numerical experiments demonstrate the superior performance of the proposed Task-RB method against the Bio-RB method under different instances.
区域限制下无人机群协同搜索与包裹投递策略
在限制飞行区域快速实现无人机群多任务解耦是保证无人机群有效性的关键。本研究在仿生规则决策算法中引入了任务切换机制,建立了行为规则到任务模式的映射关系。建立了合作搜索和包裹投递任务的完整决策模型。为了进一步提高限制区域内群体的搜索效率,提出了一种基于路径预测和虚拟代理相结合的边界处理策略。整个方案被称为任务驱动的基于规则的决策算法(Task-RB)。在全流仿真下对Task-RB方法进行了评价。数值实验表明,在不同情况下,Task-RB方法优于Bio-RB方法。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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