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生物集群能量高效利用机制研究综述

吴晓阳 邹尧 付强 贺威

吴晓阳, 邹尧, 付强, 贺威. 生物集群能量高效利用机制研究综述. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c230161
引用本文: 吴晓阳, 邹尧, 付强, 贺威. 生物集群能量高效利用机制研究综述. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c230161
Wu Xiao-Yang, Zou Yao, Fu Qiang, He Wei. An overview of energy efficient utilization mechanism of biological colonies. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c230161
Citation: Wu Xiao-Yang, Zou Yao, Fu Qiang, He Wei. An overview of energy efficient utilization mechanism of biological colonies. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c230161

生物集群能量高效利用机制研究综述

doi: 10.16383/j.aas.c230161
基金项目: 国家自然科学基金(62225304, 61933001, 62073028和62173031), 中央高校基本科研业务费专项资金(FRF-TP-22-003C2) 资助
详细信息
    作者简介:

    吴晓阳:北京科技大学智能科学与技术学院博士研究生. 2017年获得河北工业大学智能科学与技术学士学位. 2020年获得北京科技大学控制科学与工程硕士学位. 主要研究方向扑翼机器人. E-mail: wxy1995_jz@163.com

    邹尧:北京科技大学智能科学与技术学院教授. 2010年获得大连理工大学自动化学士学位.2016年获得北京航空航天大学控制理论与控制工程博士. 主要研究方向飞行器控制, 多智能体系统. E-mail: zouyao@ustb.edu.cn

    付强:北京科技大学智能科学与技术学院副教授. 2009年获得北京交通大学热能与动力工程学士学位.2016年获得北京航空航天大学导航、制导与控制博士. 主要研究方向视觉导航、视觉伺服和扑翼飞行机器人. 本文通信作者. E-mail: fuqiang@ustb.edu.cn

    贺威:北京科技大学智能科学与技术学院教授. 2006年获得华南理工大学自动化学院学士学位, 2011年获得新加坡国立大学电气工程与计算机科学系博士学位. 主要研究方向为仿生扑翼飞行机器人, 智能无人系统和智能控制. E-mail: weihe@ieee.org

An overview of energy efficient utilization mechanism of biological colonies

Funds: Supported by National Natural Science Foundation of China (61933001, 62225304, 62073028 and 62173031), Fundamental Research Funds for the Central Universities (FRF-TP-22-003C2)
More Information
    Author Bio:

    WU Xiao-Yang Ph. D. candidate at the School of Intelligence Science and Technology, University of Science and Technology Beijing. He received his bachelor degree at Intelligence Science and Technology, Hebei University of Technology in 2017. and his master degree from University of Science and Technology Beijing in 2020. His research interest covers flapping-wing air vehicles

    ZOU Yao Professor at the School of Intelligence Science and Technology, University of Science and Technology Beijing. He received his bachelor degree from Dalian University of Technology in 2010. and his Ph.D degree from Beihang University in 2016. His research interest covers control of air vehicles, Multi-agent system

    FU Qiang Associate professor at the School of Intelligence Science and Technology, University of Science and Technology Beijing. He received his bachelor degree from Beijing Jiaotong University in 2009. and his Ph.D degree from Beihang University in 2016. His research interests covers vision-based navigation, visual servoing, and flapping-wing aerial vehicles. Corresponding author of this paper

    HE Wei Professor at the School of Intelligence Science and Technology, University of Science and Technology Beijing. He received his bachelor degree from College of Automation Science and Engineering, South China University of Technology (SCUT), China in 2006, and his Ph.D. degree from Department of Electrical & Computer Engineering, National University of Singapore (NUS), Singapore in 2011. His research interest covers flapping-wing robot, intelligent unmanned system and intelligent control

  • 摘要: 近年来, 智能体集群的能量高效利用机制已经成为多智能体系统领域的热点问题, 如何使用有限的能量资源实现系统性能最优是该问题的核心研究内容. 考虑到智能体集群与生物族群的相似性, 探究生物族群的能量高效利用机制对提升智能体集群节能性能有着重要的研究价值. 为此介绍了不同生物族群中蕴含的能量利用机制, 并根据节能方式的差异分成三类, 流体优势利用机制、流体阻碍克服机制和热量交换与扩散机制, 然后对这些机制进行总结与分析, 并提出一种具有一般性的能量高效利用模型. 最后, 探讨了能量高效利用机制在多智能体系统应用中面临的挑战和发展趋势.
    1)  11 本文中流体是指, 生物族群长期生存的液体(海水)和气体(空气)
  • 图  1  迁徙鸟群的线性编队方式

    Fig.  1  Line formation of migratory birds

    图  2  鸟群编队的诱导阻力比率(引自文献[27])

    Fig.  2  Induced power ratio of different formation flight (Referred from reference [27]).

    图  3  相邻鸟类间的“翼尖间距”、“深度”和“扑翼相位差”定义

    Fig.  3  Definitions of “Wing Tip Spacing”, “Depth” and “Flapping Wing Phase”

    图  4  鸟群“V型”编队示意图

    Fig.  4  Bird flock with V-configuration formation

    图  5  鸟群能量利用率与集群规模$ n $和翼间间距$ s $的关系

    Fig.  5  Relationship between EEU of bird flock and the size $ n $ and wing tip spacing $ s $

    图  6  有鳍鱼类的“菱形”编队

    Fig.  6  Diamond formation of fish school

    图  7  鱼群节能区域及节能效果图

    Fig.  7  Energy saving zone and energy saving effect of fish school

    图  8  “菱形”编队参数示意图

    Fig.  8  Schematic diagram of diamond formation parameters

    图  9  鳗鱼游动方式(图左), 有鳍鱼类游动方式(图右)(引自文献[28])

    Fig.  9  Swimming method of eel (Picture left) and fish (Picture right)(Referred from reference [28])

    图  10  “菱形”编队示意图

    Fig.  10  Diamond formation of experiment

    图  11  EEU实验结果

    Fig.  11  Result of EEU experiment

    图  12  南极磷虾集群 (A不同规模生物群体在聚集和分散情况下的能耗情况(引自文献[104]); B磷虾运动时流体扰动的影响(引自文献[105]); C磷虾群中不同的编队方式(引自文献[109]))

    Fig.  12  Krill swarm (A Energy consumption of different group in non-swarming and swarming condition (Referred from reference [104]); B Hydrodynamic disturbance from the motion of krill(Referred from reference [105]); C Different formation method of krill swarm (Focal krill, FK)(Referred from reference [109]))

    图  13  不同规模的棘刺龙虾队列(引自文献[120])

    Fig.  13  Different sizes of migrating lobsters (Referred from reference [120])

    图  14  三叶虫集群 (A首尾相连的三叶虫队列(引自文献[128]); B线性的三叶虫队列(引自文献[130]); C非线性的三叶虫集群(引自文献[130]))

    Fig.  14  Trilobite clusters (A Queue with most individuals oriented head-under-tail (Referred from reference [128]); B Linear autochthonous trilobite clusters(Referred from reference [130]); C Nonlinear trilobite clusters.(Referred from reference [130]))

    图  15  帝企鹅群的温度分布(引自文献[116])

    Fig.  15  Temperature distribution of penguins (Referred from reference [116])

    图  16  拥挤团体EEU随团体半径$ r $(单位: 幼崽个体)的变化趋势

    Fig.  16  Relationship between EEU of huddling and radius $ r $

    表  1  多圆柱体阻力表

    Table  1  Drag coefficients of multi circle cylinders

    位置序号123456
    阻力系数1.21580.42120.21910.10690.08610.0991
    下载: 导出CSV

    表  2  多种生物族群的能量高效利用机制总结

    Table  2  Summary of energy efficient utilization mechanism in multiple biological clusters

    族群种类能量高效利用机制实验结论 (%表示)集群规模EEU模型估计节能效果参考文献
    加拿大鹅流体优势利用机制36.0%559.4%~45.3% (根据编队参数的差异)[57]
    粉红足雁流体优势利用机制14.0%549.4%~47.4% (根据编队参数的差异)[59]
    白鹈鹕流体优势利用机制11.4%~14%87.4%~28.9% (根据编队参数的差异)[62]
    鲭鱼流体优势利用机制摆动频率15.0%~29.0%14.4%~23.0% (根据编队间距的差异)[82]
    海鲈鱼流体优势利用机制摆动频率9.0%~14.0%914.4%~23.0% (根据编队间距的差异)[83]
    欧洲拟鲤流体优势利用机制摆动频率7.3%~11.6%814.4%~23.0% (根据编队间距的差异)[54]
    鲻鱼流体优势利用机制摆动频率10.5%~27.0%814.4%~23.0% (根据编队间距的差异)[87]
    鳗鱼流体优势利用机制耗氧量30.0%714.4%~23.0% (根据编队间距的差异)[96]
    南极磷虾流体优势利用机制耗氧量小7.2倍[104]
    棘刺龙虾流体阻碍克服机制65.0%阻力减免1970.6% (6只组成的队列)[117]
    三叶虫流体阻碍克服机制330.6% (2只组成的队列)[129]
    帝企鹅热量交换与扩散机制51.0%最大节能效率不超过55.0%[138]
    啮齿类动物幼崽热量交换与扩散机制100最大节能效率不超过55.0%[148, 149]
    下载: 导出CSV
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