多自治水下机器人多任务分配的自组织算法  

Task assignment algorithm of multi-AUV based on self-organizing map

作　　者：朱大奇[1] 李欣[1] 颜明重[1] 

机构地区：[1]上海海事大学水下机器人与智能系统实验室,上海201306

出　　处：《控制与决策》2012年第8期1201-1205,1210,共6页Control and Decision

基　　金：国家自然科学基金项目(51075257);上海市科委创新行动计划项目(10550502700);高校博士点基金项目(20093121110001)

摘　　要：针对自治水下机器人(AUV)研究中的多机器人多任务分配问题,提出一种基于自组织映射(SOM)神经网络的多AUV多目标分配策略.将目标点的位置坐标作为SOM神经网络的输入向量进行自组织竞争计算,输出为对应的AUV机器人,从而控制一组AUV在不同的地点完成不同的任务,使机器人按照优化的路径规则到达指定的目标位置.为了表明所提出算法的有效性,给出了二维、三维作业环境中的仿真实验结果.Aiming to the task assignment issue of multi-AUV（autonomous underwater vehicles） system, a self-organizing map（SOM） neural network based strategy of task assignment of multi-AUV and multi-objective is presented. Targets＇ locations are set as input vectors of SOM neural network. Then self-organizing competitive calculations are carded out. Its output vectors are the corresponding AUV robots＇ locations, so that a group of AUVs can be controlled to complete different tasks in different locations, and the robots can reach the designated targets in optimized paths. Simulation results in two-dimensional and three-dimensional working environments show the effectiveness of the proposed method.

关 键 词：自组织映射 神经网络 多机器人系统 自治水下机器人 任务分配 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]