基于动态蚁群劳动分工模型的多AUV任务分配方法研究
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西北工业大学

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中图分类号:TP301.6

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An Ant-Colony-Labor-Division-Model-Based Multi-AUV Dynamic Task Allocation Method
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Northwestern Polytechnical University

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    摘要:

    多水下自主航行器(Autonomous Underwater Vehicle,AUV)的动态任务分配问题具有高度非线性、动态不确定性以及多模态的特征,对多AUV 任务分配方法的自组织性、鲁棒性以及快速性提出了更高的要求。动态蚁群劳动分工(Dynamic Ant Colony’s Labor Division, DACLD)模型是一种采用分布式框架的群智能算法,众多行为简单的个体相互作用过程中涌现产生的整体智能行为能很好地适应复杂多变的环境,在解决任务分配问题上具有很好的柔性。本文引入动态蚁群劳动分工中的刺激—响应原理,建立了动态蚁群劳动分工与多AUV任务分配问题之间的映射关系,将任务的状态预测纳入响应阈值,研究了基于动态蚁群劳动分工模型的多AUV任务分配方法。同时针对任务分配过程中可能出现的任务冲突现象,提出了新的循环竞争方案以实现最大限度地利用AUV资源。仿真结果表明所提出的方法能高效地完成任务分配过程,具有很好的自组织性、鲁棒性及快速性。

    Abstract:

    The problem of dynamic task allocation for AUVs(Autonomous Underwater Vehicle) has high nonlinearity, uncertainty and multi-modal characteristics, which requires that the task allocation method has self-organization, robustness and rapidity.The Dynamic Ant Colony’s Labor Division (DACLD) mechanism is a group intelligence algorithm applying a distributed framework.The overall intelligent behavior that emerges from many simple interactions can be well adapted to complex and variable environment, which is very flexible in solving the problem of task allocation problem.This paper presents a multi-AUV task allocation method based on DACLD, in which the stimulus-response principle of ant colony division of labor is introduced and, the mapping relationship between ant colony division of labor and multi-AUV task assignment is established, and the task state estimations are incorporated into the response threshold.And also, a new cyclic competition scheme is proposed to maximize the utilization of AUV resources for the task conflict phenomenon.The simulation results show that the proposed method can efficiently complete the task allocation process and has good self-organization, robustness and rapidity.

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  • 收稿日期:2019-09-18
  • 最后修改日期:2020-10-23
  • 录用日期:2020-11-05
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