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基于蚁群算法的群机器人自组织聚集行为建模
引用本文:杨卫,曾亮,康新晨.基于蚁群算法的群机器人自组织聚集行为建模[J].系统仿真学报,2020,32(2):191-200.
作者姓名:杨卫  曾亮  康新晨
作者单位:1. 中北大学电子测试技术重点实验室,山西 太原 030051;2. 中北大学仪器科学与动态测试教育部重点实验室,山西 太原 030051
基金项目:山西省高等学校科技创新项目(18002605)
摘    要:针对群机器人聚集行为模式的形成,建立了基于质点系力学系统、以及感知状态加权的自组织运动模型,实现了机器人运动状态的自主转移建立了关于聚集行为的聚集度、均匀度等评价指标,通过实验分析比较不同模型的聚集性能,为群机器人自组织聚集行为模式的形成奠定了基础。使用分析选定的模型,对有边界约束和无边界约束2种情况进行了自组织聚集行为仿真试验,实现了不同群体规模的最大范围的有效覆盖感知,验证了模型的正确性。

关 键 词:蚁群算法  群机器人  自组织  聚集  运动模型  
收稿时间:2017-11-28

Self-organizing Aggregation Behavior Modeling of Swarm Robots Based on Ant Colony Algorithm
Yang Wei,Zeng Liang,Kang Xinchen.Self-organizing Aggregation Behavior Modeling of Swarm Robots Based on Ant Colony Algorithm[J].Journal of System Simulation,2020,32(2):191-200.
Authors:Yang Wei  Zeng Liang  Kang Xinchen
Institution:1. Science and Technology on Electronic Test & Measurement Laboratory, North University of China, Taiyuan 030051, China;2. Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education, North University of China, Taiyuan 030051, China
Abstract:Aiming at the formation of aggregation behavior model of swarm robots, a self-organizing motion model based on particle system mechanics and perceptual state weighting is established to realize the autonomous transfer of robot motion state. The aggregation degree and uniformity index of aggregation behavior are established, and the aggregation performances of different models are analyzed by experiment, which lay a foundation for the formation of self-organized aggregation behavior model of swarm robots. Using the selected model, the self-organizing aggregation behavior simulation experiments are conducted in two cases with boundary constraints and no boundary constraints. The maximum coverage of different groups of scale is realized, and the correctness of the model is verified.
Keywords:ant colony algorithm  swarm robots  self-organization  aggregation  motion model  
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