Visually guided swarm motion coordination via insect-inspired small target motion reactions.

IF 3.1 3区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY Bioinspiration & Biomimetics Pub Date : 2024-08-06 DOI:10.1088/1748-3190/ad6726
Md Arif Billah, Imraan A Faruque
{"title":"Visually guided swarm motion coordination via insect-inspired small target motion reactions.","authors":"Md Arif Billah, Imraan A Faruque","doi":"10.1088/1748-3190/ad6726","DOIUrl":null,"url":null,"abstract":"<p><p>Despite progress developing experimentally-consistent models of insect in-flight sensing and feedback for individual agents, a lack of systematic understanding of the multi-agent and group performance of the resulting bio-inspired sensing and feedback approaches remains a barrier to robotic swarm implementations. This study introduces the small-target motion reactive (STMR) swarming approach by designing a concise engineering model of the small target motion detector (STMD) neurons found in insect lobula complexes. The STMD neuron model identifies the bearing angle at which peak optic flow magnitude occurs, and this angle is used to design an output feedback switched control system. A theoretical stability analysis provides bi-agent stability and state boundedness in group contexts. The approach is simulated and implemented on ground vehicles for validation and behavioral studies. The results indicate despite having the lowest connectivity of contemporary approaches (each agent instantaneously regards only a single neighbor), STMR achieves collective group motion. STMR group level metric analysis also highlights continuously varying polarization and decreasing heading variance.</p>","PeriodicalId":55377,"journal":{"name":"Bioinspiration & Biomimetics","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinspiration & Biomimetics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1088/1748-3190/ad6726","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Despite progress developing experimentally-consistent models of insect in-flight sensing and feedback for individual agents, a lack of systematic understanding of the multi-agent and group performance of the resulting bio-inspired sensing and feedback approaches remains a barrier to robotic swarm implementations. This study introduces the small-target motion reactive (STMR) swarming approach by designing a concise engineering model of the small target motion detector (STMD) neurons found in insect lobula complexes. The STMD neuron model identifies the bearing angle at which peak optic flow magnitude occurs, and this angle is used to design an output feedback switched control system. A theoretical stability analysis provides bi-agent stability and state boundedness in group contexts. The approach is simulated and implemented on ground vehicles for validation and behavioral studies. The results indicate despite having the lowest connectivity of contemporary approaches (each agent instantaneously regards only a single neighbor), STMR achieves collective group motion. STMR group level metric analysis also highlights continuously varying polarization and decreasing heading variance.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过昆虫启发的小目标运动反应实现视觉引导的蜂群运动协调。
尽管在为单个昆虫开发与实验一致的飞行中传感和反馈模型方面取得了进展,但对由此产生的生物启发传感和反馈方法的多昆虫和群体性能缺乏系统的了解,仍然是实现机器人蜂群的一个障碍。本研究通过设计昆虫小叶复合体中的小目标运动检测器(STMD)神经元的简明工程模型,介绍了小目标运动反应(STMR)蜂群方法。STMD 神经元模型确定了出现峰值光流幅度的方位角,并利用该角度设计了一个输出反馈开关控制系统。理论稳定性分析提供了双代理稳定性和群组情况下的状态约束性。该方法在地面车辆上进行了模拟和实施,以进行验证和行为研究。结果表明,尽管该方法的连通性在同类方法中最低(每个代理仅能瞬时看到单个邻居),但仍能实现群体集体运动。STMR 群体级度量分析还凸显了持续变化的极化和不断减小的航向方差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Bioinspiration & Biomimetics
Bioinspiration & Biomimetics 工程技术-材料科学:生物材料
CiteScore
5.90
自引率
14.70%
发文量
132
审稿时长
3 months
期刊介绍: Bioinspiration & Biomimetics publishes research involving the study and distillation of principles and functions found in biological systems that have been developed through evolution, and application of this knowledge to produce novel and exciting basic technologies and new approaches to solving scientific problems. It provides a forum for interdisciplinary research which acts as a pipeline, facilitating the two-way flow of ideas and understanding between the extensive bodies of knowledge of the different disciplines. It has two principal aims: to draw on biology to enrich engineering and to draw from engineering to enrich biology. The journal aims to include input from across all intersecting areas of both fields. In biology, this would include work in all fields from physiology to ecology, with either zoological or botanical focus. In engineering, this would include both design and practical application of biomimetic or bioinspired devices and systems. Typical areas of interest include: Systems, designs and structure Communication and navigation Cooperative behaviour Self-organizing biological systems Self-healing and self-assembly Aerial locomotion and aerospace applications of biomimetics Biomorphic surface and subsurface systems Marine dynamics: swimming and underwater dynamics Applications of novel materials Biomechanics; including movement, locomotion, fluidics Cellular behaviour Sensors and senses Biomimetic or bioinformed approaches to geological exploration.
期刊最新文献
Enhancing postural stability in musculoskeletal quadrupedal locomotion through tension feedback for CPG-based controller. One-shot manufacturable soft-robotic pump inspired by embryonic tubular heart. Role of viscoelasticity in the adhesion of mushroom-shaped pillars. A biomimetic fruit fly robot for studying the neuromechanics of legged locomotion. Encoding spatiotemporal asymmetry in artificial cilia with a ctenophore-inspired soft-robotic platform.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1